Data Based Decision Making in Manufacturing Supply Chains N. Viswanadham

Transcription

1 Manufacturing Supply Chains N. Viswanadham IGSTC workshop on Strategies and Concepts for Advanced Manufacturing Computer Science and Automation Indian Institute of Science, Bangalore January 23-24, 2014

2 Contents High Performance Supply Chains Big Data Ecosystem Framework Governance Conclusions

3 High Performance Supply Chains

4 Integrated Supply Chain Network Information Network Supply Network Supplier Supplier Service Network Manufacturer Logistics Network Logistics Hub Service Provider Enterprise System or Web-site Demand Network Distributor Retailer Financial Network Banks

5 Consolidation and Connectedness 37 banks have merged to become just four JPMorgan Chase, Bank of America, Wells Fargo and Citi Group. Ten mega corporations control the output of almost everything you buy; from household products to pet food to jeans. High concentration Clusters and connected networks are highly vulnerable

6 Triggers of Global Supply Chain Disruptions

7 The Great Trade Collapse G L O B A L T R A D E Globalization & Highly Connected Supply Chains amplified & transmitted market collapse across the globe. Organizations extraneous to Supply Chain (Governments, Traders, Energy,.. Social, Political factors) influence its performance The Great Trade Collapse: Causes, Consequences and Prospects A VoxEU.org Publication Edited by Richard Baldwin page 3

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9 Big Data Fireflies on each component N. Viswanadham

10 Recent Advances:Internet of Things,.. IoT technologies can be categorized into Tagging things, Sensing things and Embedded things. The tagging things provide item identification, things can be connected to the databases. The sensing things enable us to measure and detect changes in the physical status of our environment. The embedded things yield information about the status of the embedding object. Cyber Physical Systems Systems of Systems: comprise of multiple, autonomous, embedded diverse global complex systems. Network of Networks

11 Big data Enables Cognitive Supply Chains During the last decade ERP, CRP etc analyzed internal data sales, shipments, inventory, etc. Now companies analyze external data to gain insights into customer fancies, markets, partner ecosystem and possible risks & consequences, etc Many Devices gather and store data: mobile, TVs, cars, Web, social media, traffic & security cameras, etc Data is in several forms: Images, sensor outputs, GPS, Internet of Things, text from , blogs and reviews. Data on political, social, economic, meteorological factors

12 Big data Enabled Business Processes Big Data in Supply Chains Procurement: Supplier & logistics provider selection, manufacturing locations, Delivery scheduling & Inventory management, Cost & Risk Evaluation,. Dispersed Cognitive Manufacturing: Smart Factories, Embedded Machines, Smart parts, Cognitive PLCs Distribution & Retail: Warehousing, Packaging, Tagging B2C Logistics, Customer preferences from recommender systems, In store customer moving & buying patterns Service Chains: Logistics networks, Repair & Maintenance of Machines, Fleet of Trucks, Aircrafts, etc Risk Mitigation Processes: Mitigating Cascading of network failures, Self Adaptive Machines, etc

13 Big data should aid in Decision Making that results in Desired Business Outcomes In Global supply chains, "What is the most sought after customer value, and what marriage of data and algorithms gets us there?" The Big Question is what data from suppliers, customers, governments, and local & economic environment should one collect and process to get desired business outcomes. What data you analyze every day, every week, every month. A framework is needed to answer this question

14 Ecosystem Framework N. Viswanadham

15 The Basic Ecosystem Institutions Resources Delivery Services Infrastructure Supply Chain Investment Climate Co-Evolution, Risk Propagation Ecosystem Aware Global Supply Chain Management

16 Customs, Export & Trade Other Govt. Regulators Quality Control & Environmental Issues Social, Legal and Privacy issues,labor Unions Logistics & IT companies Delivery Channels INSTITUTIONS Infrastructure: Ports, Airports, Roads, Cloud and other storage resources Decision Making Tools, BPO, Control Towers IOT and Cognitive control systems DELIVERY SERVICE MECHANISMS SUPPLY CHAIN ECOSYSTEM RESOURCES Industry Clusters, Social Media, Web Blogs, Recommender systems Human, Financial & Natural Resources Location Factors SUPPLY CHAIN Retail Chains Distribution Manufacturing Suppliers

17 SES Framework Can Help To Study Governance Risk Innovation Performance

18 Governance Hierarchy, Market or Network N. Viswanadham

19 Three Types of Network Governance Supply Chain networks are Globally dispersed, independent organizations, connected only through Service agreements, Internet, FIIs, etc The Network Governance model Highly Centralized External Broker (Li & Fung, Olam Intl.) Participant Shared Governance by Elected Board (Healthcare, Dairies, Cooperatives) Participant Shared Governance with a Lead Player Producer-driven (Cisco, Nike) Buyer-driven (Wal-Mart, Carrefour, Levi) All three governance forms are in practice.

20 Governance: Partner Selection, Coordination & Control A separate chain is formed for each order Partner selection based on Transaction Cost and the risks in the ecosystem Coordination : Determining who does what and when and communicating to everyone Execution: Monitor order status so that processes work as per plan & control exceptional events

21 Data Based Governance: Partner selection, Coordination & Execution Other Agencies Coordination Partner Selection

22 Risks in the Ecosystem Sr. No Risk classification Risk Elements R1 R2 R3 R4 R5 Supply Chain Location risk Outsourcing risk Design, manufacturing defects, Inventory deficit Delay or unavailability of materials from suppliers Breakdown of machines, power failure R6 Raw material, Human, Financial R7 Social unrest, War Resources R8 Infrastructure deficit, talent shortage R9 Credit squeeze, Energy & water shortage R10 Regulatory risk R11 Political Institutional R12 Labor issues R13 Trade agreements R14 R15 R16 R17 Delivery infrastructure Failure of IT infrastructure SC visibility decreases Inbound and outbound logistics failure Failure of governance mechanism

23 Supplier Selection using Transaction Costs Delivery Resource Institutions Supply Chain Shipping, Inventory, Asset specific Hard & Soft Infrastructure Asset Specific Clusters, Human, Financial, Power Taxes, Tariffs, SEZs, FTAs, Social groups Production, Quality, Transport Coordination Costs Broker fees Transaction Cost

24 Coordination Coordination is to bring different complex activities or organizations into a harmonious relationship. The coordination includes For every order, selection of suppliers; assigning functions to them such as what to supply, how is it to be produced (e.g., product tolerances and process standards), the production and delivery schedules, etc Identifying key parameters such as the product specification, the technology and the quality systems, labor and environmental standards along with the targeted price and communicating to the chain partners.

25 Supply Chain Control Tower A command centre for visibility, decisionmaking, and action, based on real-time data. Concept that has been around for a while in logistics called 4PL Make real time decisions (exceptions) based on data

26 Conclusions New technology developments such as IOT, cloud computing, mobile devices; Internet, Cognitive control, Big data analytics have immense impact on performance & competitiveness. Our framework identifies the data to collect and analyze to make the needed decisions The same methodology can be used to analyze service value networks and public networks for infrastructure building and food security. Talent is need of the hour.

27 Mathematical Models for Design of Governance Mechanisms The partner selection problem can be formulated as Fuzzy AHP or MIP problem. One can rank order the suppliers for each component based on the ecosystem parameters based on TCE. Coordination, scheduling problems can be solved using Optimization techniques Expert systems, Decision support systems, Case based reasoning and Hybrid control systems are useful for Exception Management and Execution

28 Big Data in Supply Chains