Quantified Closed Quality Control (QC)² Project Proposal for the Sixth CORNET Call
Decisions From Top-Management to Shop-Floor are Based on an Incomplete Set of Information Initial Situation and Challenge Quality Stream Quality Forward Chains Quality Backward Chain Data Distribution Products Field Data The majority of manufacturing companies is currently facing global trends and inevitable consequences like individual and dynamic product demands, enhanced market transparency and legal restrictions Especially SMEs can not expend to plan all probable states or to invest in costly activities like fire fighting or specialized task forces OEMs use to bear the consequences of dynamics SMEs essential benefit of quick and flexible reaction to individual customer request is often outweighed by uncertain or fuzzy information due to losses throughout the own value or related supply chains Mostly these information gaps appear where flows are not shaped, slowed down or stopped as a result of unforeseen situations or unplanned activities Additionally the customer is unwilling to pay for more than an expected quality level. Hence in the product dimension a control of quality is rather be needed than a maximization The operationalization of information flows not only regarding product but also process and system quality enable SMEs to close the aforementioned gaps and face global challenges lastingly Seite 2
Quality Control Loops are Suitable to Operationalize the Needed Information Flows for Closing the Existing Gaps Hypothesis z y - e x w Robust and quantifiable closed quality control loops allow companies to identify, use and distribute needed information Complex interactions in value chains can be modeled and combined to closed quality control loops Quality control loops describe the interaction of organization, factors of production and information flows with the objective of controlled quality including effective and efficient processes and workflows Quality is an adjustable value, which is embodied by various parameters and needs to be determined from multiple perspectives. The objective is not to maximize quality but to control it along the value chain Independent technical control loops and organizational continuous improvement processes are insufficient for the task of controlling quality A sufficient closed quality control loop structure needs to be designed from an organizational and an technical perspective Seite 3
The Design of a Quality Control Loop Structure for Manufacturing Companies Needs Scientific and Industrial Expertise Project Approach Research Partner A Cybernetics SME RWTH Aachen University Production Technology Project Coordination Collaborative Research SME Research Partner B Information Technology SME Besides scientific research in the fields of production technology, cybernetics and information management industrial expertise is needed Focussed disciplines are e.g. quality management, production systems, control loop theories and business information systems Scientific and industrial quality control loops have to be structured, classified and assessed in order to identify generic structures Objective of the project is a set of blueprints for quality control loops including generic reference, error, feedback and desired parameters as well as guidelines for company specific adaption The holistic project approach is based on the scientific and industrial expertise of production technology, cybernetics and information technology Seite 4
The Definition of Research Tasks is Derived from a Multi-Perspective View on the Heuristic Framework Scientific Approach Information Technology Perspectives Production Technology Cybernetics Research task Value Chain Initial Situation, Challenge and Hypothesis Heuristic framework Management Systems The scientific program is based on the initial situation, the challenge and particularly the hypothesis The three perspectives allow a synthesized problem solving approach from different scientific domains The heuristic framework contains and describes fundamental aspects and concepts of the object domain The view from the scientific perspectives to the object domain deduces specific research task The depicted scientific approach needs to be enlarged by validation in small and medium sized companies in order to guarantee the industrial relevance Quality Closed Control Information Loops Software Application Scientific Program Cornet Project Quantified Closed Quality Control (QC²) Seite 5
The Three Research Institutes Cooperate with SMEs to Synthesize Scientific and Industrial Research Competences Collaborative Approach Research task -Scientific definition of quality control loops Perspectives Production Technology Heuristic framework Management Systems Value Chain Quality - Development of a modelling approach for quality control loops Information Technology Cybernetics Closed Control Loops Software Application Initial Situation, Challenge and Hypothesis Information deductiv - Development of guidelines for the assessment of stability and effectiveness of quality control loops & Cooperating Research Institutes SMEs from each participating country inductiv - Prototypical implementation and validation of developed methods and tools Blueprints for Quality Control Loops - Description of generic quality control structures and types - Definition of SMEs requirements concerning the use of quality control loops Seite 6
The Three Research Institutes Represent the Different Perspectives Within the Proposed Research Project x y x y?? Profile Research Partner A Expertise in control loop engineering and cybernetics Project Role Research Partner A Cybernetics Representation of the systems control view into the project work Transfer of state of the art approaches of control loop engineering to engineering management problems RWTH Aachen University Production Technology Project Coordination Profile Laboratory for Machine Tools and Production Engineering WZL Expertise in production and quality management Project Role Representing the production technology and integrating all views Project coordination and transfer of production research, methods and approaches Research Partner B Information Technology Profile Research Partner B Expertise in information management and the development of IT-systems Project Role Representation of the information management view Transfer of approaches, tools and methods from the field of information technology to the project Seite 7
Contact Dipl.-Ing. Christoph Hammers Business Excellence & Development Department Quality Management Chair of Metrology and Quality Management Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University Phone.: +49 (241) 80-24178 Fax: +49 (241) 80-22193 Mail: c.hammers@wzl.rwth-aachen.de Dipl.-Ing. Dipl.-Wirt. Ing. Patrick Beaujean Customer Satisfaction & Operations Management Department Quality Management Chair of Metrology and Quality Management Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University Phone.: +49 (241) 80-26339 Fax: +49 (241) 80-22193 Mail: p.beaujean@wzl.rwth-aachen.de Seite 8