Advanced Manufacturing Systems and Enterprises

University of Minho School of Engineering Advanced Manufacturing Systems and Enterprises Goran D. Putnik, Hélio Castro, Luís Ferreira, Rui Barbosa, Gaspar Vieira, Cátia Alves, Vaibhav Shah, Zlata Putnik, Maria Manuela Cruz-Cunha, Leonilde Varela

Goran D. Putnik, Hélio Castro, Luís Ferreira, Rui Barbosa, Gaspar Vieira, Cátia Alves, Vaibhav Shah, Zlata Putnik, Maria Manuela Cruz-Cunha, Leonilde Varela Advanced Manufacturing Systems and Enterprises Towards Ubiquitous and Cloud Manufacturing University of Minho School of Engineering

Reproduction is authorised provided the source is acknowledged. Any use made of the information in this document is entirely at the user's risk. No liability will be accepted by the authors. Title: Advanced Manufacturing Systems and Enterprises Subtitle: Towards Ubiquitous and Cloud Manufacturing Authors: Goran D. Putnik, Hélio Castro, Luís Ferreira, Rui Barbosa, Gaspar Vieira, Cátia Alves, Vaibhav Shah, Zlata Putnik, Maria Manuela Cruz-Cunha, Leonilde Varela Copyright 2012 by Goran Putnik First Edition: October 2012 Publishing company: University of Minho School of Engineering Review: LabVE Print by: Copissaurio Repro, Lda. Distribution by: LabVE University of Minho, School of Engineering, Department of Production and Systems Engineering

iii Acknowledgments Creating a book is a hard, but compensating and enriching, task. It involves an array of different activities, such as book development process management, organization and integration of contents, technical editing of book, contacts with printing company, distribution and other activities, and finally, virtually the most important task, interaction with readers, in order to achieve the most important object of creating a book that meets public expectations. All these activities are not possible without resources and collaboration of many parties. The authors would like to acknowledge the help, support and confidence of all those who made this creation possible. We are also grateful to other members of the research group on Distributed and Virtual Manufacturing Systems and Enterprises (DVMSE) and the Laboratory for Virtual Enterprises (LabVE), of the Centre for Industrial and Technology Management (CGIT), who are not among the authors of this book, but who were helping always when it was necessary. Special thanks go to our institutions, the University of Minho and Centre for Industrial and Technology Management (CGIT), in Portugal, for providing the material resources and all necessary logistics. The authors wish to acknowledge the support of: 1) The Foundation for Science and Technology FCT, Project PTDC/EME-GIN/102143/2008, Ubiquitous oriented embedded systems for globally distributed factories of manufacturing enterprises, 2) EUREKA, Project E! 4177-Pro-Factory UES. Authors, Guimarães, September 2012

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v Preface About the subject This book addresses the development of advanced manufacturing systems and enterprises in response to the nowadays requirements for new industrialization, manufacturing revitalization (The White House President Barack Obama, 2009), job crisis resolution through new manufacturing, manufacturing renaissance and similar, as a vision on manufacturing as virtually indispensable instrument for nowadays global economic crisis resolution. The concept of Ubiquitous and Cloud Manufacturing Systems (UCMS), the subject of this book, is expected to deliver the next generation of methods and means for enabling modern manufacturing enterprises capable to respond to the above mentioned requirements. The next generation of methods and means for enabling modern manufacturing enterprises should be characterized by the synergetic effects that come from the domains of a) innovative management and control architecture, b) distributed systems of ICT, and c) ubiquitous oriented embedded systems. The focus of research presented in this book is on the following technological contributions:: 1) Development of an organisational model for the UCMS, and a corresponding infrastructure, based on a pilot laboratory workshop, which will comprise organisational infrastructures for providing higher level supporting services for the UCMS object manufacturing and business processes. The main purpose of this infrastructure is to provide a higher degree of UCMS robustness in terms of interoperability, re-configurability and agility, efficiency and effectiveness. The special focuses are on services and tools for UCMS organisational network development - the human role and relationship in a UCMS, as the most important part of an organisation: roles spanning from equipment operators to high level management.

vi 2) Testing of the organisational model of the UCMS, and its infrastructure, based on the pilot laboratory workshop. The research results presented in the book are developed within the Ubiquitous oriented embedded systems for globally distributed factories of manufacturing enterprises project, reference PTDC/EME-GIN/102143/2008, funded by the Portuguese Foundation for Science and Technology (FCT), and approved as EUREKA project, reference E! 4177 UES. Organization of the book The book is consisted of two main parts. The first part is organized through 5 chapters, of which the first chapter makes an introduction in the subject, the second chapter presents the concepts of ubiquity, clouds, services systems and the global idea of ubiquitous and cloud manufacturing, in the third chapter an architecture of ubiquitous and cloud manufacturing system is provided, the fourth chapter presents a pilot installation in laboratorial environment, and, finally the fifth chapter presents the conclusions. The second part consists of 5 annexes that provide more details on technical and implementation aspects of the prototype model and the pilot installation developed. Expectation The book provides researchers, scholars and professionals with some of the most advanced research developments, solutions and implementations. It is expected to provide a better understanding of advanced manufacturing systems and enterprises and their implementation as ubiquitous and cloud manufacturing, in order to achieve the expected and necessary transformative changes towards true sustainability. We expect the book to be read by academics (i.e., teachers, researchers and students), technology solutions developers and enterprise managers (including top-level managers), and, specially, by entrepreneurs. The book is also expected to help and support teachers of graduate and postgraduate courses from management, industrial engineering and mechanical engineering to ICT. Also, the authors believe that the concepts of ubiquitous and cloud manufacturing may influence the actual education practices, in both domains - university education and professional education, influencing both the course contents (curricula) and the education technology itself. Authors, Guimarães, September 2012

vii Contents Acknowledgments Preface Chapter I Introduction: In search of new manufacturing system paradigms 3 Chapter II Ubiquity, Clouds, Services Systems and Ubiquitous and Cloud Manufacturing 11 Ubiquitous Systems 12 Clouds 14 Manufacturing as service systems 16 Ubiquitous and cloud production network idealization 18 Chapter III Ubiquitous and Cloud Manufacturing: An Architecture 23 Service system architecture 23 ICT platform architecture 26 iii v Chapter IV A Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing adoption in Industry and Community 4 UCMS laboratorial platform as a learning factory 41 Platform s functional architecture and its implementation 48 Chapter V Conclusions 55 References 59 Annexes 63 Annex I: Distributed Informatics System for Manufacturing: Specification and Architecture Hybrid architecture Client-Server + P2P 67 Annex II: Distributed Informatics System for Manufacturing: Specification and Architecture Cloud-based Architecture 83

viii Annex III: Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing System - Hybrid Architecture 97 Annex IV: Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing System - Cloud-based Architecture 111 Annex V: Pilot Laboratorial Plant for Ubiquitous and Cloud Manufacturing Systems 129

Advanced Manufacturing Systems and Enterprises Towards Ubiquitous and Cloud Manufacturing

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3 Chapter I Introduction: In search of new manufacturing system paradigms The traditional Manufacturing was superseded. The new dynamic and global business model forced traditional production processes to change, in the sense of integrating them in a global chain of resources and stakeholders. The agility, quick reaction to market changes and proactivity are essential, and the high availability and capacity to effectively answer to requirements are some of the main competitiveness and sustainability criterion. Additionally, new challenges have emerged, such as - reallocation of manufacturing jobs, declination of a number of manufacturing jobs, emergence of new industries, environmental. For example, in (The White House President Barack Obama, 2009) one of the challenges is described in the following words: Manufacturing workers have paradoxically often been victims of their sector s own success, as rapid productivity growth has meant that goods can be produced with fewer workers, contributing to a several decades-long trend of declining employment. This trend has been compounded by the shift of consumer spending from manufactured goods like TVs and cars to services like tourism, dining out and healthcare as well as increased consumption of manufacturing goods made elsewhere. And the recent downturn has been particularly painful for manufacturing companies, their workers and the communities that rely on them.

4 The challenge of reallocation of manufacturing jobs emerges because of - overall costs drive manufacturers location choices. In today's increasingly competitive global marketplace, manufacturing activities will be undertaken by private actors who will locate their factories where total all-in cost is lowest. (ibid.). It is hard to believe that the concentration of, virtually, all manufacturing in a couple of countries, e.g., metaphorically, in a couple of Asian countries now and in a couple of European countries in the past, is beneficial to the whole world. While areas that have concentration of manufacturing activity experience benefits for virtually all, including companies, workers and communities, the areas that lose manufacturing jobs are heavily affected as well, albeit negatively. For example, Communities that experience substantial declines in manufacturing activity experience losses in county population, slower growth in the number of housing units and increases in the local poverty rate. The adjustment to these losses is slow and remains incomplete even decades later (ibid.), and similar. Equally, the manufacturing job loss creates great negative impacts on individual levels, on manufacturing workers.

Figure 1.1 - Short term EU emission profile compared to 2ºC compatible long term target (p. 40) (European Commission, 2010b) 5

6 The environmental challenges are similarly dramatic. Concerning the quantitative measures, by the Kyoto Protocol, European Community s commitment was to reduce 8% of the quantity of emission (p. 21, Annex B) (United Nations, 1998). Later, in 2007, The European Council emphasizes that the EU is committed to transforming Europe into a highly energyefficient and low greenhouse-gas-emitting economy and decides that, ( ) the EU makes a firm independent commitment to achieve at least a 20 % reduction of greenhouse gas emissions by 2020 compared to 1990. (p. 13) (European Council, 2007). But To have a reasonable chance of staying below the 2 C threshold, global GHG emissions must be reduced to less than 50% of 1990 levels by 2050 (p.3) (Commission of the European Communities, 2009). Additionally, EU offers to scale up the reduction to 30% if other developed and developing countries agree to take a fair share of the global reduction. It means, further, that the previously established target is still insufficient to achieve the long term objective of keeping the average global temperature increase below 2 C by 2050. In order to pursue this objective, developed countries must point their emission targets for a reduction in the order of 80% to 95% by 2050 as compared to in 1990. (European Commission, 2010a) In other words, it would be necessary to accelerate the implementation of all mechanisms for GHG reduction, especially after 2030 in order to compensate lower rate of effort up to 2030. This is graphically presented in Figure 1.1 (European Commission, 2010a). Concerning the effort needed to respond to the challenge, according to WWF, The good news is, we have the technology to start to fix the problem. (WWF, 2010). The third global challenge is already well known global financial crisis specially accentuated in Europe.

Figure 1.2 Number of papers by manufacturing concepts and year 7

8 All these three global challenges, the social, environmental and economical, are parts of the issue of sustainability. Solutions to these challenges require a great set of new mechanisms spanning from legislations and regulations (national, regional, international, global), social, cultural, organizational, to technology advances. Some of the instruments that are expected to contribute to answering the above mentioned challenges are new manufacturing paradigms, in which context we are presenting research intensification on recently proposed manufacturing paradigms. In parallel, we are witnessing an intensive search for new manufacturing paradigms too. Both parameters grow in numbers. In literature, a number of designations could be found, such as: Ubiquitous Manufacturing Enterprise Interoperability Networked Enterprise Lean Production/Manufacturing Global Manufacturing Mass Customization Reconfigurable Manufacturing Systems Collaborative Engineering Manufacturing Supply Chain Virtual Enterprise Enterprise Integration Agile Manufacturing Real-time Enterprises Concurrent Engineering Sustainable Manufacturing Life Cycle Management Remanufacturing Digital Manufacturing Cloud Manufacturing Just In Time manufacturing Flexible Manufacturing Open Manufacturing Craft Manufacturing All-embracing manufacturing Learning Factory Extended Enterprise Production Network Grid Manufacturing Micro Factory Social Network Manufacturing Desktop Factory Pocket Factory Fit Manufacturing Virtual Organization In Figure 1.2, a number of papers in collections of some of the World leading publishers (Elsevier, Springer, Emerald, ACM, IEEE) per year and per manufacturing concepts listed above is shown, presenting growing intensity of research

9 on, and on a number of newly proposed, or emerging, manufacturing concepts. Equally, a great number of research projects on the above referred manufacturing concepts, or those that generated new manufacturing concepts, were financed by a number of national and international research programmes (for example, the well-known EC Frameworks Programmes in Europe such as FP7 and future Horizon 2020). Some of the above mentioned manufacturing concepts hypothesize on inter-enterprise networking as one of the most promising instruments to face the big sustainability challenges, relying on exploration of so-called network effects. Network effects occur when to an economic agent, e.g., a consumer of a firm, the utility of using a product or technology becomes larger as its network of users grows in size (Farrell & Saloner, 1985; Katz & Shapiro, 1985). The network effect may set in motion a positive feedback loop that will cause a product or technology to become more prevalent in the market. (Den Hartigh, 2005). Besides the network effects alone, as the positive feedback loop instrument, extremely interesting is their combination with other phenomena, namely, social interaction effects, scale effects and learning effects, that could be considered as other positive feedback loop instruments, which (the combination) may, and is expected to, create the increasing return effect.

10 Increasing returns are the opposite phenomena to the well-known law of decreasing returns in economy. The increasing returns occur when the output of an economic system increases more than proportionally with a rise of input (Den Hartigh, 2005). The importance of designing and investigating increasing returns mechanisms are multiple (ibid): 1) there is growing evidence that increasing returns actually do exist, at least in the relevant business domain of firms ; 2) it is becoming more relevant in the increasingly information and knowledge based business environment of today especially considering information products and service sectors; and 3) the presence of increasing returns seems to be a precondition for economic growth to occur at all. The paradigm of Ubiquitous and Cloud Manufacturing, whose architecture and implementation framework are presented in this book, is seen as an instrument for manufacturing organizational and productive capacity transformation, to contribute for the above mentioned sustainability challenges. Ubiquitous and Cloud Manufacturing is a network based system conceived to enable a combination of network effects, social interaction effects, scale effects and learning effects, in order to further enable the positive feedback loop in the form of increasing return as a virtual precondition for the needed economic growth, as well as, the positive feedback loop in the context of other two big sustainability challenges, namely, environmental and social.

11 Chapter II Ubiquity, Clouds, Services Systems and Ubiquitous and Cloud Manufacturing Globalization, innovation and ICT (Information and Communication Technologies) are transforming many sectors to anywhere, anytime platforms, towards an intelligent business model under design anywhere, make anywhere, and sell anywhere paradigm (Elliott, 2010). We would add anytime too. Traditional stakeholders (suppliers and customers) are transformed in services, where supplying or using profiles are a question of needs or context. One service (a Calculator, for instance) can execute (supply) something using other services (Addition, Subtraction, Multiplication and Division operations) (Usmani, Azeem, Samreen, 2011). Many of the existent infra-structures are already ubiquitous and/or cloud based, or are changing towards these virtual architectures. To efficiently use those infra-structures the applications must be transformed and follow services oriented applications pattern.

12 Ubiquitous Systems Ubiquity is a synonym for omnipresence, the property of being present everywhere 1 The state or quality of being, or appearing to be, everywhere at once; actual or perceived omnipresence. Omnipresence: the ability to be at all places at the same time; usually only attributed to God 2. According to Weiser (1993) Ubiquitous Computing represents: Long-term the PC and workstation will wither because computing access will be everywhere: in the walls, on wrists, and in scrap computers (like scrap paper) lying about to be grabbed as needed. Weiser also used a powerful term: calm technology, as another description of Ubiquitous Systems. Computing technology has evolved up to the point when Ubiquitous Computing System development and operation are possible, using present network devices, protocols and applications. On the other hand, ubiquity has been addressed in relation to manufacturing systems as well. In (Foust, 1975) the term ubiquitous is explicitly defined to be functional in an empirical context ( ) The types of manufacturing which are both market oriented and have a frequency of occurrence greater than a specific limit which can be empirically defined are ubiquitous.. Foust (1975) cites Alfred Weber s definition of ubiquitous manufacturing too: Ubiquity naturally does not mean that a commodity is present or producible at every mathematical point of the country or region. It means that the commodity is so extensively available within the region that, wherever a place of consumption is located, there are ( ) opportunities for producing it in the vicinity. Ubiquity is therefore not a mathematical, but a practical and approximate, term (praktischernaherungsbegriff). 1 Wikipédia: http://en.wikipedia.org/wiki/ubiquity 2 Wiktionary: https://pt.wiktionary.org/wiki/ubiquity

13 Figure 2.1 Types of Product-Service Systems (Meier H., Roy R., Seliger G., 2010) Figure 2.2 Industrial Product-Service Systems scientific fields of action (redrawn from Meier H., Roy R., Seliger G., 2010)

14 Clouds Definition of cloud is reinforced by (Group, E., 2010) - as the reference source created within the EC initiative and, therefore, it is the most relevant for an Advanced Manufacturing Systems and/or Enterprise. A cloud is a platform or infrastructure that enables execution of code (services, applications etc.), in a managed and elastic fashion, whereas managed means that reliability according to pre-defined quality parameters is automatically ensured and elastic implies that the resources are put to use according to actual current requirements observing overarching requirement definitions implicitly, elasticity includes both up- and downward scalability of resources and data, but also load-balancing of data throughput. Cloud has a number of particular characteristics that distinguish it from classical resource and service provisioning environments: (1) it is (virtually) infinitely scalable; (2) it provides one or more of an infrastructure for platforms, a platform for applications or applications (via services) themselves; (3) thus clouds can be used for every purpose from disaster recovery/business continuity through to a fully outsourced ICT service for an organisation; (4) clouds shift the costs for a business opportunity from CAPEX to OPEX which allows finer control of expenditure maintenance reducing the entry threshold barrier; (5) currently the major cloud providers have already invested in large scale infrastructure and now offer a cloud service to exploit it; (6) as a consequence the cloud offerings are heterogeneous and without agreed interfaces; (7) cloud providers essentially provide datacentres for outsourcing; (8) there are concerns over security if a business places its valuable knowledge, information and data on an external service; (9) there are concerns over availability and business continuity with some recent examples of failures; (10) there are concerns over data shipping over anticipated broadband speeds. (Group, E., 2010).

15 Figure 2.3 a) UMS has UCS as an operating system Ubiquity of Computational resources only; b) UMS operates as UCS Ubiquity of all Resources: Material processing, Knowledge, and Computational resources Figure 2.4 Ubiquitous and cloud manufacturing network idealization using cloud platform

16 Concerning the EU policy towards clouds, the document refers two main recommendations: Recommendation 1: The EC should stimulate research and technological development in the area of Cloud Computing, Recommendation 2: The EC together with Member States should set up the right regulatory framework to facilitate the uptake of Cloud computing. Concerning the types of clouds, for an Advanced Manufacturing Systems and/or Enterprise, the most important are the concepts of cloud types: 1. IaaS - Infrastructure as a Service, 2. PaaS - Platform as a Service, 3. SaaS - Software as a Service, and 4. collectively *aas (Everything as a Service) all of which imply a service-oriented architecture, which includes, e.g., MaaS Manufacturing as a Service. Manufacturing as service systems Definition of the manufacturing as a service system was conceived primarily by the requirements for new business models in manufacturing and not in relation to clouds. However, cloud has provided a new view and capacity on/for manufacturing as service systems. Manufacturing as the service system is related to the concept of Industrial and Product- Service Systems. Industrial and Product-Service Systems (IPS2) represents a paradigm shift from the separated consideration of products and services to a new product understanding consisting of integrated products and services [that] creates innovation potential to increase the sustainable competitiveness of mechanical engineering and plant design. The latter allows business models which do not focus on the machine sales but on the use for the customer, e.g. in form of continuously available machines. The business model determines the complexity of delivery processes. Characteristics of Industrial Product- Service Systems allow covering all market demands (Meier H., Roy R., Seliger G., 2010).

Figure 2.5 A service architecture for the Ubiquitous and Cloud Production implementation 17

18 Considering the Industrial and Product-Service Systems approach, different sets, larger or smaller, of these services are already offered by different manufacturers such as, Mori Seiki Co. LTD. enterprise integrating services of training, square parts, field services, hotline and remote services (Meier H., Roy R., Seliger G., 2010). There are three types of Product-Service Systems (Figure 2.1): 1. Service Products service engineering considers product and service as an independent goods; 2. Extended Products - service engineering is machine oriented, i.e., service is a product extension; 3. Industrial Product-Service System - simultaneous and interfering product and; 4. Service engineering. Industrial Product-Service Systems scientific fields of action are presented in Figure 2.2. Ubiquitous and cloud production network idealization Considering the Ubiquitous Systems and Cloud based platform concepts, an idea of distributed, complex, scalable, and we can say, democratic network was projected, that allows enterprises and individuals entrepreneurs to adjust their market position in a sustainable and competitive way. To the above mentioned definitions (by (Foust, 1975) and (Weber, 1928)), which consider ubiquity of resources anywhere, we add the ubiquity in time anytime, which (the anytime ), from its side, implies the dynamic, on-line, seamless, enterprises organizational and manufacturing system networking and reconfigurability, or adaptability, that requires new organisational architectures and metaenterprise organizations as creating and operating environments, makes the UMS a true new paradigm. Virtually, any product domain can be transformed functionally into a Product- Service System. The transformation of a concrete product into a transformation Product-Service System depends, in reality, of other factors, such as social and economic factors.

Figure 2.6 Figurative presentation of VE evolution: from conservative, minimal network domain, e.g. of the traditional supply chain architecture (a), towards ubiquitous network domain (d). 19

20 All these features are considered in Ubiquitous and Cloud Manufacturing concepts. We suggest an advanced manufacturing system in which Ubiquitous and Cloud Computing is mapped with direct adoption of ubiquitous and cloud computing technologies. In this context, resources are seen, essentially, as services that can create a network. This manufacturing service-oriented network can stimulate production oriented to service-oriented manufacturing (Cheng et al., 2010). Therefore, Ubiquitous Manufacturing Systems and Enterprises concept is related to the availability of management, control and operation functions of manufacturing systems and enterprises anywhere, anytime, using direct control, notebooks or handheld devices. It is related with Ubiquitous Computing Systems. Ubiquitous Manufacturing Systems (UMS), therefore, implies ubiquity of three general types of resources in organizations: Material processing resources (e.g. machine tools and other manufacturing/production equipment as resources); Information processing resources (e.g. computational resources includes hardware and software, and services creation); and Knowledge resources (i.e. human resources, considering the humans as unique resources for knowledge generation and new products and, at the end, the ultimate effectiveness of organisations). However, there are two quite different approaches to the concept of UMS. The first concept considers ubiquity of the MS based on, i.e. using, the ubiquitous computational systems (UCS) (see Figure 2.3 (a)); The second one, which is originally our approach, considers ubiquity of the MS as a homomorphism, i.e. it is a mapping, of the ubiquitous computational systems (UCS), (see Figure 2.3 (b)), (Putnik et al., 2004), (Putnik et al., 2006), (Putnik et al., 2007). The similar idea was referred in Murakami & Fujinuma (2000), (cited by Serrano & Fischer; 2007). This approach is referred also as Ubiquitous networking that emphasises the possibility of building networks of persons and objects for sending and receiving information of all kinds and thus providing the users with services anytime and at any place. A ubiquitous and cloud manufacturing network idealization using cloud platform in European

21 geographic space is presented in Figure 2.4. Figure 2.5 shows a framework for services architecture construction to support the Ubiquitous and Cloud Production, or Ubiquitous and Cloud Manufacturing, development and implementation. Some hypothesis on UMS The hypothesis is that UMS should be based on a hyper -sized manufacturing network, consisting of thousands, hundreds of thousands, or millions of nodes, i.e. of manufacturing resources units, freely accessible and independent, Figure 2.6. 4) These UMS hyper -sized manufacturing networks could be seen as manufacturing resources Internet of Things, 5) These UMS hyper -sized manufacturing networks could be seen as manufacturing production social networks, enabling advanced and emerging organizational and business models based on crowdsourcing, open source products, open source economy, and others, 6) These UMS hyper -sized manufacturing networks form and use clouds, and others. Further implications are that 1) UMS manufacturing units should be, in the limit, primitive, i.e. individuals, or individual companies, and individually owned hardware/software resources, 2) Management and operation of UMS should be informed by the discipline of chaos and complexity management in organizations, e.g. Chaordic System Thinking (CST) model (Eijnatten et al, 2007), 3) Specific instruments should be used, such as meta-organizations (e.g. Market of Resources model), brokering and virtuality,

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23 Chapter III Ubiquitous and Cloud Manufacturing: an Architecture Service system architecture As referred in the previous chapter, considering the Ubiquitous Systems and Cloud based platform concepts, an idea of distributed, complex, scalable, and we can say, a democratic network was projected, that allows enterprises and individuals entrepreneurs to adjust and project (referring to reactivity and proactivity, respectively) their market position in a sustainable and competitive way. Thus, the services of real time data acquisition (through intelligent production monitoring services), product design and production management services, are distributed in a global network of resources (enterprises and individuals entrepreneurs) that provide these services. These services will be supported by a cloud infrastructure. The platform architecture is a projection of the supporting architecture for Ubiquitous and Cloud Manufacturing Systems, in which the manufacturing system corresponds functionally to a service system. That is, the ubiquitous manufacturing system architecture. Figure 3.1, is a cloud based architecture that represents the manufacturing system as a service system, integrating the services for: 1) Real-time Data Acquisition Services for real-time data acquisition from the equipment through the embedded intelligent information devices services type: Equipment Intelligent Monitoring Systems, 2) Product Design Services, that integrates four environments: a) Computer Aided Design, b) Product data repository with embedded Intelligent System for Decision Making (for accessing all relevant data, actual and historic as well as data analysis) from the equipment in use, c) Mixed-reality Environment, and d) Co-Creation (Collaborative) Environment for co-creative design services type: Product Design Services ;

24 3) Equipment Operation Services, that integrates four environments: a) Equipment Data Real-time with embedded Intelligent System for Decision Making, that provides all relevant data, actual and historic as well as data analysis and management suggestions, necessary for the production management b) Management environment, for monitoring, scheduling and controlling management activities, with embedded Intelligent System for Decision Making, c) Mixed-reality Environment, and d) Co-Creation (Collaborative) Environment for co-creative management services types: Production Management Services and Production Planning and Control Services ; 4) The cloud infrastructure, that will provide the a) infrastructure for the manufacturing system applications of all three types of resources: material processing resources, information processing resources (i.e. computational resources), and knowledge resources in the form of IaaS - Infrastructure as a Service (including manufacturing resources as a service in the form of MaaS), b) platform for the manufacturing system applications in the form of PaaS - Platform as a Service, and c) manufacturing system software business applications in the form of SaaS - Software as a Service. For the architecture presented in Figure 3.1, the possible technological support platform oriented to the cloud, is presented in Figure 3.2.

Figure 3.1 Overall system architecture for development, implementation and validation 25

26 ICT platform architecture The logical architecture of the ICT Platform is architecture for integration of Representation, Mixed-reality representation, Real-time management model, and Communication for collaborative management. It is basically a 3-tier layer architecture consisting of (1) Presentation Layer, (2) Business Layer and (3) Data Layer: 1) The Presentation Layer represents/defines applications and support for all interfaces, views, presentations and communications for users. 2) The Business Layer represents/defines applications and support for all business applications such as Decision Making applications, Intelligent System applications, Services Workflows. 3) The Data Layer represents/defines applications and support for all applications for data repository and management, including knowledge bases (e.g. for Intelligent System on the upper level). For each layer the corresponding technology to be employed is referred. Each logic layer interacts with the other using appropriate interoperability services. Its implementation is supported by technologies capable and duly integrated into the 'cloud'. A view of the architecture is presented on Figure 3.3. Furthermore, some functional modules, which belong to the Business Layer, are presented.

Figure 3.2 Technological support platform oriented to the cloud 27

28 Co-Creation platform: Semiotics and Pragmatics, Co-Design, Co-Management, and Co-* Semiotics and Pragmatics In its most simple definition, semiotics is the science of signs. The domain of semiotics comprises three fields: syntax, semantics and pragmatics. While syntax and semantics are well known in the Manufacturing Systems (MS) science, pragmatics is almost totally unknown as a discipline. The universally accepted order among the three semiotic fields, introduced by Carnap (1942), is based on their degree of abstractness in relation to complete signs and semiosis: If in an investigation explicit reference is made to the speaker, or, to put it in more general terms, to the user of language, then we assign it to the field of pragmatics. If we abstract from the user of the language and analyse only the expressions and their designate, we are in the field of semantics. And if, finally, we abstract from the designate also and analyse only the relations between the expressions, we are in (logical) syntax. (Carnap 1942: 9). This criterion could be considered of the maximum importance as it reveals proximity to the reality of syntactics, semantics and pragmatics (Putnik G.D., Putnik Z., 2010). The relevance of the semiotic approach in a social context in engineering has emerged in response to the failure of the traditional technocentric approach to today s information systems (IS) and organisations requirements as well as to the software development crisis. (ibid.). In other words, the relevance of the semiotic approach could be clearer if considering that the biggest problem is in fact data interpretation. Actually, the data interpretation depends at the end only of humans and implementing semiotics/pragmatics directly addresses this problem and introduces the instrument for its treatment.

29 Presentation Layer Communication o Audio chat o Audio conference o Video chat o Video conference o Messenger o Others Resources o Management o Data o Mixed-Reality o Geo-reference o Video o Others Technology: JQuery, HTML5, CSS3 XMPP Frameworks: OpenSimulator/SilverLight Business Layer Tools o Co-Creation (Co-Design, Co-Management, Co-Maintenance, ) o Audio conference o Mixed-Reality o Video conference o Intelligent Systems o Others o Brokering o Selection and Reconfiguration o Sustainability Technology: Web Services / RESTful API Cloud API (SaaS) Data Layer Tools o Quering o Selection o Refinement Technology: Web Services / RESTful API LINQ Cloud API (SaaS) DBMS Figure 3.3 ICT Platform Architecture

30 A vision of introduction of the semiotics/pragmatics concept as an instrument is shown in the Figure 3.4. The semiotics approach, and in particular pragmatics, in UCMS is additionally enhanced through introduction of the concept of Co- Creation. Co-Creation Co-Creation is already relatively in regular use, especially in marketing and some design practices and in these disciplines it refers a joint design of product by designer and costumer. This is relatively close to the traditional Concurrent Engineering concept and practices. However, the semantics is quite different from theory to theory, from author to author, from user -group to user -group, from community to community. Even in the scientific literature there are contradictory definitions. Not entering here in discussion on the cocreation, or co-creativity or co-design or coevolution, models and definitions, the interpretation of co-creation assumed in UCMS is that co-creation process means that, in the minimal, or elementary configuration, there are two agents (minimum) that cocreatively construct their product, whether the product is a design of a new equipment (with embedded intelligent information devices) or e.g. a (predictive) maintenance action ( while the traditional design / management / control paradigm is a 1:1 relation). It means that these activities and decision are co-constructed, or cocreated, by a group of designers and/or managers, in order to achieve increased cognitive capacity of agents, designers or managers, and other stakeholders, in order to enable and ensure faster and better decisions and higher level coherence with the reality, which is another objective (and performance measure). This approach, the co-creation or co-creativity or co-design or co-evolution, is also in accordance with recently promoted semiotics based manufacturing system integration which is, simplifying, a communicational based system, rather than information transaction based. Collaboration (in design and management processes) enables and ensures better decisions by increasing the cognitive capacity of designers and/or managers and other stakeholders and higher level coherence with the reality through implementation of co-creative management. In other terms, the collaborative design/management paradigm is oriented towards effectiveness, rather than towards efficiency, as the effectiveness is nowadays the problem of the higher impact in organizations.

31 Figure 3.4 Interfaces for communication in a MS Cell with both pragmatic and semantic communication channels (Putnik G.D., Putnik Z., 2010) Figure 3.5 A video conferencing environment for traditional 1:1 architecture of design and/or management process Figure 3.6 A video conferencing environment for cocreative oriented n:n architecture of design and/or management process Figure 3.7 Future cyber-commons environment (Leigh & Brown, 2008)

32 Figure 3.5 and Figure 3.6 present the traditional 1:1 architecture of design and/or management process, and the co-creative oriented n:n architecture of design and/or management process (in a virtual, i.e. multivideo conferencing environment) respectively. Figure 3.7 shows an advanced and complex environment denominated as cyber-commons environment, as another implementation for co-creation environment. Advanced manufacturing system architecture will integrate environments, or so-called, cocreative platforms, for three co-creative environments: 1) Product design processes, 2) Operation, or production, management processes, and 3) Integrated design-production processes. It means that the co-creative processes, in both groups of agents, will perform independently, i.e. the designers will be capable to perform their processes in their own environment separately from the managers 1st Co- Creative cycle (Design Co-Creation), and the managers will be capable to perform their processes in their own environment separately from the designers 2nd Co-Creative cycle (Management Co-Creation). However, additionally, both groups will be capable to perform their processes jointly in a fully integrated and systemic way 3rd Co-Creative cycle (Integrated Co-Creation), Figure 3.8. The supporting technology will be based on multi-user video-conferencing with auxiliary functionalities. A vision is presented on the Figure 3.9. These three cycles, and the video-conferencing environment, will provide full semiotic/pragmatics effects and support in order to enhance the cognitive and creative capacities of the participants to the maximum, and a full co-creative, or co-design or coevolving, and truly systemic environment. Mixed-reality platform Mixed Reality is defined as "...anywhere between the extrema of the virtuality continuum.", (Milgram P., Kishino A. F., 1994), where the Virtuality Continuum (VC) extends from the completely real through to the completely virtual environment with augmented reality and augmented virtuality ranging between, Figure 3.10.

Figure 3.8 Advanced manufacturing system co-creative platform, for three co-creative environments: 1) for product design processes, 2) for operation, or production, management processes, and 3) for integrated design-production processes. 33

34 The conventionally held view of a Virtual Reality (VR) environment is one in which the participant-observer is totally immersed in, and able to interact with, a completely synthetic world. Such a world may mimic the properties of some real-world environments, either existing or fictional; however, it can also exceed the bounds of physical reality by creating a world in which the physical laws ordinarily governing space, time, mechanics, material properties, etc. no longer hold. What may be overlooked in this view, however, is that the VR label is also frequently used in association with a variety of other environments, to which total immersion and complete synthesis do not necessarily pertain, but which fall somewhere along a virtuality continuum. a particular subclass of VR related technologies that involve the merging of real and virtual worlds, which we refer to generically as Mixed Reality (MR). Mixed-reality technologies are used, concerning engineering and production, in a number of advanced applications of design, training, validation, control, management, marketing, etc. Within UCMS mixed-reality technologies will be used for both (1) new generation products and equipment design with embedded intelligent information devices (for advancing production performance and other functions e.g. reliability and maintainability), creating virtual reality environment of the workshops and equipment for enhancing design performance and quality, as well as for (2) production management (including planning and control) services, in which the manager will supervise the workshops and equipment over virtual reality models of the workshop or through the video monitoring enriched by e.g. virtual tags with relevant information attached to each equipment in the workshop. A vision for application of the mixed-reality technologies presented in Figure 3.11, Figure 3.12 and Figure 3.13 shows a vision of the manufacturing system environment, combining the mixed-reality platform with co-creative platform, and other relevant environments. The mixed-reality platform could be developed following the concepts of metaverse environments, i.e. the mixed-reality platform could be developed over a 3D metaverse platform such as OpenSimulator (opensimulator.org) or SecondLife (secondlife.com). 3D Application Servers such as OpenSimulator (opensimulator.org) or SecondLife (secondlife.com) provide a fast track to developing virtual worlds. They seem to be a natural choice for the development of the

35 Figure 3.11 Virtual reality Figure 3.9 A vision of the multi-user video-conferencing system as the co-creative environment Figure 3.12 Mixed reality - with virtual tags only Figure 3.10 Reality-Virtuality continuum (Milgram & Kishino, 1994) Figure 3.13 Mixed reality Augmented Reality form

36 type of prototype we are aiming at. OpenSimulator, in particular, has the advantage of being open source. This means the backend can be programmed, making it highly configurable and extensible. An additional challenge is to render the objects of the automatically generated environments more realistically, both regarding their 3D look and feel and the details of their behaviour, while conforming to the high level model. Interactive evolutionary computation approaches have been used to speed the design process in application areas ranging from facial image generation, graphics, and 3D lighting to industrial design (an extensive review can be found in literature). The challenges in this process include finding an adequate parametric model of the object to be generated, an algorithm to navigate the parameter space, and an assessment function which often includes user input. For example, genetics-based algorithms have been used to prototype virtual objects and to automatically generate applications. In particular, the challenge is to find parametric models of the 3D objects and their behaviour and to assess the usefulness of this evolutionary computation approach. The platform should support both implicit and explicit interactions. Implicit interactions happen through virtual sensors that capture, for example, the position of the user in the space. Explicit interactions imply the availability of virtual devices presented in the simulation. For example, touch screens or simulated portable devices. Intelligent System UCMS should implement a series of software application for employment of intelligent algorithms for diverse objectives such as evaluation of behavioural curves in real-time, pattern recognition, data mining, etc. These techniques are to be combined with other relevant techniques. Sustainability There are a number of sustainability definitions depending on the context. However, this is a critical issue for the society as a whole and for many communities in particular. Besides the differences, large number of communities, and especially governmental bodies, agree that the sustainability should address three challenges, Figure 3.14 (Jovane F., 2007): economical challenges, by producing wealth and new services ensuring

37 Figure 3.14 Fundamentals of sustainable development (Jovane F., 2007) Figure 3.15 Sustainable value-creating modules in a global network (Seliger G, et al., 2008)

38 development and competitiveness through time; environmental challenges, by promoting minimal use of natural resources (in particular non-renewable) and managing them in the best possible way while reducing environmental impact; social challenges, by promoting social development and improved quality of life through renewed quality of wealth and jobs. (Jovane et al., 2008). It means that UCMS should consciously address all three challenges. The issues such as Products What, Organization When, Where, Production Facilities By and HUMANS are mandatory to address, Figure 3.15 (Seliger G, et al., 2008). At the field level, UCM products and services must be: safe and ecologically sound throughout their life cycle (environmental challenge); appropriately designed equipment to be durable, repairable, readily recycled, compostable, or easily biodegradable (economical and environmental challenge); produced and used in production to reduce the energy costs and environmental pollution by a factor of minimum 20% (economical and environmental challenge); capable of new jobs creation (social challenge)!

39 The proposed architecture addresses the three aspects of sustainability: economic, environmental and social, implementing them in the following way: Economic and environmental sustainability: Economic and environmental sustainability is based on implementation of specific software modules, with corresponding analytical models, for continuous evaluation of energy consumption and costs, environmental pollution and associated costs. These models and applications will be embedded in data acquisition services. Social sustainability: Advanced manufacturing system components support Social sustainability goals enabling The creation of new jobs This effect is possible because the advanced manufacturing system is conceived as a service system meaning a great degree of openness for performing these services, the maintenance management and design services, by individuals ( free-lancers ), micro and small companies, that would form a dynamic network of services providers. In this way a potential for new jobs creation will be dramatically increased.

40

41 Chapter IV A Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing Adoption in Industry and Community UCMS laboratorial platform as a learning factory Competitiveness, innovation and sustainability, internationalization and factories globally distributed, networked businesses, real time management and information and communication technologies, as well as new business models, are terms that have been directly or indirectly embedded throughout the previous chapters. The concepts of Ubiquitous and Cloud Manufacturing were explored, by presenting a model of advanced manufacturing systems and enterprises, as well as an architecture that is able to support it. Although the idea of collaboration between partners and enterprises, or even the collaboration into a distributed network, and the use of advanced ICT, may seem simple and clear, and can represent an incentive for the industry to ensure greater competitiveness and sustainability by companies, the truth is that, it is unclear how this interrelation works, as well as what is the exact role of various stakeholders including customers, products and services suppliers, 'Brokers' and Meta Organization.

42 In this way, a laboratory platform, that integrates physical components, was created, as a complex computational solution, capable of simulating network operations, and representing a pilot installation of UCMS. The objective of this laboratorial platform is to serve as a learning factory platform to ensure the adoption of the ubiquitous and cloud manufacturing concepts in industry and community, through training and through carrying out real business operations in reduced volume of services. Thus, the developed platform has two general functionalities: (1) as a learning factory - to increase competences, skills, know-how, and to be a bridge for competences, skills, know-how exchange, and (2) as a new business generator - to transform the traditional enterprises into future enterprises. In other words, this laboratorial platform, as learning factory, allows the entrepreneurs, manufacturing factories and enterprises to work in network, communicate, and make decisions in real time, through new technologies and new organizational forms. Thus, with this new type of work and business environment, new products and businesses can emerge among the users with the final objective to achieve the desired competitiveness and sustainability.

Figure 4.1 A Learning Factory Platform applicability in industry and community 43

44 Although the concept of Learning Factory is not very recent, the innovative platform s dimension is the application of the Learning Factory concept for Ubiquitous and Cloud Manufacturing as the Advanced Manufacturing Systems and Enterprises agents for the XXI Century. The laboratorial platform, as learning factory, allows the enterprises and the community to learn and train the ubiquitous and cloud concepts applicability (Figure 4.1), promoting entrepreneurship and creation of new business models. The mission of the Learning Factory is to integrate design, manufacturing and business realities into engineering education. This is accomplished by providing a state-of-the-art, hands-on active learning laboratory, a practice-based curriculum, and real (industrydriven) projects. (Lamancusa & Simpson, 2004) The Learning Factory is a paradigm shift to industry-partnered, interdisciplinary, realworld problem solving in engineering education. (Lamancusa et al. 2008)

Figure 4.2 A laboratorial pilot installation of a UCMS and as a UCMS learning factory environment 45

46 In industry, companies can use the platform internally, for training their own personnel in service-based manufacturing, product-service systems, working over the Internet, and generating competences on UCMS principles performing manufacturing services anytime, anywhere. Companies can also use the platform externally by performing learning and training jointly with other companies through exchanging services and creation of addedvalue with other companies and through small projects development with community (in the first place with academia, but also with other social groups, e.g. cooperating with employment centres for personnel requalification, and similar). Use of the platform for external and internal learning and training are also applicable in the community through e.g. students curricular activities (internal) and development of their projects within the laboratory and among themselves only internal learning and training, or in cooperation with, and in, companies external learning and training. This type of training also promotes entrepreneurship to solve the unemployment, which is a critical issue for young people who start their professional career.

47 Figure 4.3 Resource Environment Figure 4.3 UCMS Client s control room Figure 4.5 Extended physical platform, as a Learning Factory of ubiquitous and cloud manufacturing Figure 4.6 Informal demonstrator architecture

48 Platform s functional architecture and its implementation The laboratory platform was developed by the University of Minho in the Laboratory of Virtual Enterprises (LabVE) - Guimarães, Portugal. In Figure 4.2 the laboratorial platform s physical installation is shown, as a pilot installation of UCMS, and as a UCMS learning factory environment. The installed platform (Figure 4.2) can be extended with physical facilities into different modules: Client, Broker and Resource (Figure 4.5), anywhere, in any institution, whether academic or industrial, fixed or mobile, creating a real true and physical ubiquitous and cloud manufacturing learning factory. Figure 4.3 and Figure 4.4 show one of the machining resource, i.e. UCMS server s, environment desktop machine-tools and its communicational interface, and the UCMS control room UCMS client s environment and its large-screen communicational interface for creation of virtual presence environments, respectively.

49 a) b) c) d) Figure 4.7 Frontends: a) Meta-organization, b) Client, c) Broker e d) Resource Figure 4.8 Meta-Organization module Figure 4.9 Meta-Organization module: Dashboards for Quality and Trust Management Figure 4.10 Client modules

50 Additionally, the installed platform can be extended with virtual equipment modules that can be installed in any computer to simulate a machine tool operation, and in that way, possibly to create real large networks for advanced experimentation and training. Thus, the developed platform corresponds to the logical architecture implementation of the ubiquitous and cloud manufacturing concept (Figure 4.6), able to simulate the concept similar to a very near future industrial reality, that would be based on Ubiquitous and Cloud Manufacturing. Platform Computational and Functional Modules The laboratorial platform, as a UCMS pilot installation and learning factory, has four computational modules for the four types of system agents: Meta-Organization, Customer, Broker and Resource. Figure 4.7 presents the four laboratorial platform computational modules frontends. Meta-Organization is an environment to facilitate and manage the efficient dynamic UCMS network reconfiguration and particular UCMS execution networks, and to ensure virtuality, as one of the dynamic reconfiguration tools, with low transaction costs, low confidentiality risks, protection of knowledge, trust management (Cunha & Putnik, 2008). The Meta-Organization manages the network environment, since the registration till the contract termination, ensuring the information confidentiality, trust and ethics between the customers, service and products providers, and manages Brokers too (Figure 4.8). The metaorganization manager is responsible for metaorganization trust, quality and metaorganization operations management, and has a set of dashboards (Figure 4.9) in order to help in management processes and the members of the network, and a set of communication channels chat, video conferencing, and others to all users.

51 Figure 4.11 Single Screen Desktop Environment Figure 4.12 Multiple Screens Large + Desktop Environment Figure 4.13 Mobile application frontends (for smartphones)

52 Client registers and generates new production orders, and then associates them to Brokers (that will inform on the best resources to accomplish a certain order). Similarly to the other modules, Client has a set of management tools and a set of communications channels (email, chat, video conference and others) properly embedded and integrated. At the end of each production order the Client communicates his evaluation of the Broker and Resource as the feedback within the Total Quality Management functionality, for the continuous system improvement (Figure 4.10). If the resource allows, the Client can see the production order to be/being executed by the resource, and if the Client wishes (and resource allows), he can control the resource, anywhere, anytime, from a control room, or a PC or via mobile devices (smartphone, tablets, laptops, and others). Client may use a single screen desktop environment (Figure 4.11) or may use a control room, in which it is possible to expand to large screens for control and communication, among other features (Figure 4.12). Additionally, the Client can use applications based on mobile smartphones exclusively (Figure 4.13). This ensures the essential multimodal support for applications that are intended to be ubiquitous. Broker is a middleware agent, whose principal role is the dynamic reconfiguration management. Also, he is the principal agent of agility and virtuality that acts/operates between Client and Resources (Cunha & Putnik, 2008).

53 Figure 4.14 Broker module Figure 4.15 Resource module

54 The Broker receives the incoming production orders from Clients, selects the best Resources candidates to propose to the Client. He has the ability to negotiate with the Resource, e.g., to negotiate the reference price for a particular order, through chat, e-mail and video conferencing, or other. When the order is finished, the Broker communicates his evaluation of the Client and Resource as the feedback (Figure 4.14). As referred above, if the Resource allows, the Client can see the production order to be/being executed by the Resource and can control the Resource, anywhere (when the Resource is a machine, computer, or software), using a control room, PC or via mobile devices (Figure 4.13). When the order is finished, the Resource communicates his evaluation of the Client and Broker as the feedback to the system. Resource is any provider of any service, such as machine-tools, human agents as service providers (designers, managers, machine operators, planners, schedulers, sellers, and others), computing resources, software, etc. The Resource receives and negotiates the orders received through Broker by chat, video, conferencing or e-mail. After the order approval, a direct relation is established between the Resource and the Client, and the production order is executed by the Resource (Figure 4.15).

55 Chapter V Conclusions It could be said that new manufacturing paradigms emerge. New approaches to products and services for and by industry are transforming the traditional companies organizations. The concept of Ubiquitous and Cloud Manufacturing meets the requirements for new manufacturing paradigms. It permits the existence of total availability management, control and operational functions of manufacturing systems and enterprises, anywhere, anytime, using direct control, notebooks or handheld devices. The necessity for greater capacity (usually associated with more resources) or excessive capacity "release" are behaviours associated to enterprises which join to the ubiquitous manufacturing standard. In other words, ubiquitous application must ensure responsiveness in any time and space context. On other hand, the Cloud concept and technologies boost advanced manufacturing systems and enterprises, offering platforms that enable large scales applications, on all service levels. The architecture presented is of a general nature, with structural elements and open in various aspects, in nature and in number, that enables development of an advanced manufacturing system or enterprises on different complexity levels which is one of the primary requirements for the capacity of achieving sustainability. Therefore, the architecture presented may have a number of implementation forms. It would be useful to remind that a number of underlying technologies should be considered, which were not possible to analyse in all details due to the book s limited space, e.g. embedded intelligent information devices, real-time management (and design), mixed reality and augmented reality, semiotics and pragmatics, co-creation, chaos and complexity management, the theory of sustainability, web 2.0 to web 4.0, and others.

56 Concerning the implementation framework, the Laboratorial Platform was designed with services to be interoperable in client-server, Peer-to-Peer distributed environments, and in emergent Ubiquitous and Cloud Computing. Web services availability ensures interoperability among different computing platforms and the multimodal capacity ensures its use by multiple devices. The support database are able to integrate cloud servers (Azure, Google, among others), adequately ensuring its functionality and reliability. Thus the necessary conditions for a ubiquitous and cloud manufacturing applications are properly supported. Furthermore, the Learning Factory concept implemented is an important concept for learning and training in the industry and in the community as a continuous development instrument, absolutely necessary to achieve higher levels of competitiveness and sustainability. Also, the advanced manufacturing systems and enterprises based on ubiquitous and cloud manufacturing adoption, implementation and exploitation, require new kind of jobs creation, in which each person is able to integrate in the ubiquitous and cloud manufacturing system and enterprise as a value-chain partner. With the platform development and the implementation, the conditions and future developments for an effective and efficient adoption of advanced manufacturing systems and enterprises based on ubiquitous and cloud manufacturing were created. Thus, new organizational concepts contribute, and are essential tools, to fight against local and global unemployment, which in the context of the current global crisis is also extremely important task in parallel with search for competitiveness within the sustainability challenges.

57 However, there are a number of open technical, organizational and conceptual problems that require hard work in the future. Two of the virtually most important problems to work on are the interoperability, or integration, of the Ubiquitous and Cloud Manufacturing and its adoption in society and industry. Finalizing the conclusions, some challenges mentioned in the Introduction are referred in the context of ubiquitous and cloud manufacturing contribution. It could be said that ubiquitous and cloud manufacturing directly contributes to the manufacturing jobs reallocation challenge once it ensures responsiveness in any time and space context. The ubiquitous and cloud manufacturing system s capability to provide services anywhere means it s distance independent, meaning further that it is capable to eliminate needs for physical mobility of manufacturing value-chain participants (public or private individuals transport), and in that way indirectly contributes to the environmental sustainability requirement. Additionally, as the ubiquitous and cloud manufacturing represents a form of dynamic network of service providers, with virtually the greatest degree of openness, it enables creation of new jobs, through emergence of new individual, micro and small companies, and in that way making new concentrations of manufacturing activities bringing benefits for virtually all companies, workers and communities.

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59 References Carnap, R. (1942) Introduction to semantics. Cambridge, MA: Harvard University Press Cheng, Y., Tao, F., Zhang, L., Zhang, X., Xi, G. H., & Zhao, D. (2010). Study on the utility model and utility equilibrium of resource service transaction in cloud manufacturing. Paper presented at the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Commission of the European Communities (2009). Communication from the commission to the european parliament, the council, the european economic and social committee and the committee of the regions. Towards a comprehensive climate change agreement in Copenhagen. Brussels. Cunha, Maria Manuela, Putnik, Goran D. (2008) "Market of Resources as a Knowledge Management Enabler in VE." In Knowledge Management: Concepts, Methodologies, Tools, and Applications, ed. Murray E. Jennex, 2699-2711. Den Hartigh, E. (2005). Increasing returns and firm performance: an empirical study. Doctoral thesis, Erasmus University Rotterdam, Netherlands. Eijnatten F., Putnik G., & Sluga A. (2007) Chaordic Systems Thinking for Novelty in Contemporary Manufacturing, CIRP Annals, 56(1), 447-450. Elliott, L. (2010). The Business of ICT in Manufacturing in Africa: Afribiz. European Commission (2010a). COMMISSION STAFF WORKING DOCUMENT accompanying the Communication from the Commission to the European Parliament, the Council, the european economic and social committee and the committee of the regions. Analysis of options to move beyond 20% greenhouse gas emission reductions and assessing the risk of

60 carbon leakage. Background information and analysis - Part I. Brussels, Belgium. European Council (2007). Presidency Conclusions Brussels, 8/9 March 2007. Council of the European Union. Brussels. 7224/1/07, REV 1. Foust, Brady J. (1975) Ubiquitous Manufacturing, Annals of the Association of American Geographers, 65(1), 13-17. Group, E. (2010). In K. Jeffery & B. Neidecker- Lutz(Eds.). The Future of Cloud Computing: Opportunities for European Cloud Computing behond 2010 (Europe Commission). Jovane F (2007) How to Maintain Competitiveness on the Way Towards Sustainable Manufacturing?, Tampere Manufacturing Summit, June 6 7. Jovane F., Yoshikawa H., Alting L., Boer C.R., Westkamper E., Williams D., Tseng M., Seliger G., Paci A.M. (2008) The incoming global technological and industrial revolution towards competitive sustainable manufacturing, CIRP Annals - Manufacturing Technology, 57 (2008) 641 659. Lamancusa, J. S. and Simpson, T. W., (2004). The Learning Factory - 10 Years of Impact at Penn State, International Conference on Engineering Education, Gainesville, FL, ineer, October 16-21, pp. 1-8. Lamancusa, J. S., Zayas, J. L., Soyster, A. L., Morell, L., and Jorgensen, J., (2008). The Learning Factory: Industry-Partnered Active Learning. Journal of Engineering Education; pp. 5-11. Leigh J, Brown M-D (2008) Cyber-Commons: Merging Real and Virtual Worlds. Communications of the ACM 51(1):82 85. Meier H., Roy R., & Seliger G. (2010) Industrial Product-Service Systems IPS2, CIRP Annals - Manufacturing Technology, 59, 607 627. Milgram P., Kishino A. F. (1994) Taxonomy of Mixed Reality Visual Displays, IEICE Transactions on Information and Systems, E77-D(12), pp. 1321-1329. Murakami, T., Fujinuma, A. (2000).Ubiquitous Networking: Towards a new paradigm. Nomura Research Institute Papers, No. 2. Putnik G. et al. (2004) Cells for Ubiquitous Production Systems, Proposal for R&D Project, Project reference: POSC/EIA/60210/2004, submitted to Fundação para a Ciência e a Tecnologia (FCT), Lisbon, Portugal.

61 Putnik G. et al. (2006) Ubiquitous Production Systems and Enterprises - advanced enterprise networks for competitive global manufacturing, Proposal for R&D Project, Project reference: PTDC/EME- GIN/72035/2006, submitted to Fundação para a Ciência e a Tecnologia (FCT), Lisbon, Portugal. Putnik G.D., Cardeira C., Leitão P., Restivo F., Santos J., Sluga A., & Butala P. (2007) Towards Ubiquitous Production Systems and Enterprises, in Proceedings of IEEE Int. Symp. on Ind. Electronics - ISIE 2007, Vigo, Spain. Putnik, G.D. and Putnik, Z. (2010) A semiotic framework for manufacturing systems integration -Part I: Generative integration model, International Journal of Computer Integrated Manufacturing, 23: 8, 691 709. Seliger G, Severengiz S, Weinert N (2008) Sustainable Industrial Value Creation Nets. Proceedings of the 15th CIRP International Conference on Life Cycle Engineering, March 17 19, 2008, Sydney, Australia, 1 4. Serrano V., & Fischer T. (2007) Collaborative innovation in ubiquitous systems, J Intell Manuf (2007) 18, 599 615. The White House President Barack Obama. (2009) A Framework for Revitalizing American Manufacturing. Executive Office of the President of the United States. Washington, USA. United Nations (1998). Kyoto protocol to the United Nations framework convention on climate change. Usmani, S., Azeem, N., & Samreen, A. (2011). Dynamic Service Composition in SOA and QoS Related Issues International Journal of Computer Technology and Applications, 2, 1315-1321. Weber A. (1928), Theory of the Location of Industries, translated by C. J. Friedrich (Chicago: University of Chicago Press, 1928), p. 51 (emphases by Foust, Brady J. (1975)). Weiser, http://www.ubiq.com/hypertext/weiser/ubi Home.html, Xerox PARC Sandbox Server. WWF (2010). Earth Overshoot Day how can we get out of debt? WWF news. Available from: http://www.wwf.org.uk/news_feed.cfm?417 3/Earth-Overshoot-Day--how-can-we-getout-of-debt (Accessed: 7th September 2012).

62

Annexes 63

64

65 Annex I: Distributed Informatics System for Manufacturing: Specification and Architecture Hybrid architecture Client-Server + P2P Annex II: Distributed Informatics System for Manufacturing: Specification and Architecture Cloud-based Architecture Annex III: Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing System - Hybrid Architecture Annex IV: Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing System - Cloud-based Architecture Annex V: Pilot Laboratorial Plant for Ubiquitous and Cloud Manufacturing Systems

66

67 Annex I Distributed Informatics System for Manufacturing: Specification and Architecture Hybrid architecture Client-Server + P2P

68

UMS Software Architecture Overview 69

70 Peer-to-Peer (P2P) VideoCall design

Web service: Process of communication between a client and an XML Web service 71

72 UMS Software Components: Client Functions

UMS Software Components: Resource Functions 73

74 UMS Software Components: Resource Functions

UMS Software Components: Meta-Organization Functions 75

76 UMS Software Database Server Database Architecture

UMS Broker Software Workflow 77

78 UMS Client Software Workflow

UMS Resource Software Workflow 79

80 UMS Meta Organization Software Workflow

81 Using Web Service in mobile devices Main Page of Windows Phone Application Main Page of Windows Phone Application

82

83 Annex II Distributed Informatics System for Manufacturing: Specification and Architecture Cloud-based Architecture

84

Effective Cloud based Semiotic Architecture 85

86 From Transactional to Communicational architecture Application Multimodal Client App... Portal Office Web server... Web server Platform DB Server Application Server... Application Server Data Services... MoR Other Servers Middleware Operating System Windows, Mac, etc. Vurtualized Infrastruture Storage, CPU, Network Transactional Multilayer Architecture

87 From Transactional to Communicational architecture (a) Pragmatics Platform Application Communication... Portal Office Multimodal Web server Application Server...... Web server Application Server Client App... DB Server MoR Data Services Other Servers Renderer Devices Pragmatics Renderer Renderer Server Brokering Middleware Operating System Windows, Mac, etc. Vurtualized Infrastruture Storage, CPU, Network Communicational Architecture where devices are Pragmatics Renderers

88 Multimodal interfaces for multiple Client devices classes

Communicational Architecture: Pragmatic Channels 89

90 Communicational Architecture: Technological support

Communicational Architecture: Technological Architecture - MVC/RIA Pattern 91

92 Communicational Architecture: Integrated Communications Channels

UMS Supporting Architecture 93

94 Cloud-based broker: (a) Process Plan (b) Stereotype (c) Candidate resources (d) Spatial Data in cloud O 1 O 2 O 3 O 4 O 4 (a) (b) r 1 r 2 r 3 r 4 (c) (d)

95 Cloudlet Architecture (a) Dashboards (b) Cloudlet (service) (c) Enhanced cloudlet (d) Cloudlet with pragmatics instruments (d) (c) (b) Cirrus (a)

96

97 Annex III Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing System - Hybrid Architecture

98

Create Clients Account 99

100 Main form of UMS Client

101 View - Resource Cameras Client VideoCall

102 Main form of Broker Broker VideoCall

Create Resources Account 103

104 Main form of Resource

Create Meta-Organizations Account 105

106 Main form of Meta-Organization

Quality Management: Statistics 107

108 Quality Management: Clients Feedbacks

Quality Management: Resources Feedbacks 109

110

111 Annex IV Laboratorial Platform as Learning Factory for Ubiquitous and Cloud Manufacturing System - Cloud-based Architecture

112

Resource Administration: Resources list 113

114 Resource Administration: Resources channels

Resource Administration: Resources tasks 115

116 Brokers Filters

Resources Selection 117

118 Map representation of selected of resources

119 Map InfoWindow with resource data Web Chat Channel

120 Reconfiguration Manager

Reconfiguration InfoWindows events 121

122 Reconfiguration Alternative Resources Management

Communication with Alternative Resource 123

124 Reconfiguration using the Map

125 Reconfiguration Map Resource Event Reconfiguration with Map Resource Details Reconfiguration Alternative Resource Channels

126 Mobile GUI PhoneClient Resource Registration PhoneClient Resource Channels Registration

127 Mobile GUI PhoneClient Keyboard Emulator PhoneClient Market of Resources Management

128

129 Annex V Pilot Laboratorial Plant for Ubiquitous and Cloud Manufacturing Systems

130

Descriptive Presentation 131

132 Logical Presentation

133 Physical Layout Control Room 1

134 Physical Layout Control Room 2

135 Physical Layout UMS Workshop

136 Some photos.

Some photos 137

138 Some photos

Some photos 139

140 NOTES

NOTES 141

142 NOTES

4