( MULTI-AGENT BASE ) HOLONIC SUPPLY CHAIN MANAGEMENT

( MULTI-AGENT BASE ) HOLONIC SUPPLY CHAIN MANAGEMENT By OMOJARO A. PETER MOSTAFA JAFARI MOHAMMAD KHAONJANI

OUTLINE • Abstract • Introduction • Defining supply chain management (SCM) • . Integrated supply chain network • . Basic Operation categories • . Role of information Technology • Holonic supply chain • Characteristics of Holonic/Multi agent SCM • Condition for implementation • Comparing Holonic/Multi agent SCM with Conventional SCM • Case study • Application of Virtual Reality • Conclusion

ABSTRACT This analysis presents the fields of supply chain management, multi-agent systems, and the merger of these two fields into multi-agent based supply chain management. The concept of supply chain management is to overlook and manage the transition of raw goods in to finished products. and thus, a synthesis of supply chain management and multi-agent systems introduce agents application to achieve this. For this purpose, agents are firstly, introduced as a new information technology for supply chain management before focusing on how agents can contribute to solving problems in supply chains. A compairism of supply chain management and a multi-agents base SCM is then presented followed by a case study. A look at the possibility of a virtual form of simulating the proposed model is stated.

INTRODUCTION Today ….. Market place is increasingly demanding more in term of lower cost, faster time-to-market and better quality SO Forcing companies to become ever more reactive and agile in performing their business task. Modern manufacturing should be able to act like a cell in an organism (the market). The survival of manufacturing companies has become increasingly more depended on their ability to react promptly and flexibility to market variation and need . Flexibility appear to be the strategic success factor to satisfy the global competition need of worldwide manufacturing enterprise, allowing them to provide high- quality production at reasonable cost.

TERMS DEFINATIONS Supply Chain Is the global network used to deliver products and services from raw material to end customers through an engineered flow of information, physical distribution, and cash. - The association for operation management, (APICS) Supply Chain is “the set of firms acting to design, engineer, market, manufacture, and distribute products and services to end-consumers”. In general, this set of firms is structured as a network, in which we can see a supply chain with five levels (raw material suppliers, tier suppliers, manufacturers, distribution centers and retailers). - Muckstadt and his colleague

INTERNAL SUPPLY CHAIN Purchasing Production Distribution Suppliers Customer TERMS DEFINATIONS Supply Chain Management : The Design, Maintenance, and operation of supply chain processes, including those that make up extended product features, for satisfaction of end-user needs.- James B. Ayers fig. 1 Supply Chain Operation Reference ( SCOR)

Integrated SCM : Over the years more corporations have become increasingly flexible and dependent on outsourcing the production of their goods to other corporations, who are able to do the job at a more affordable rate. This explain the different links and merging of more than one company to process and bring to existence a desired product from the raw material supplier, the tier supplier the manufacturer or assembler, distributors and final consumer. As previously explained, the concept of inter-company collaboration is a way to create such synergies in a supply chain.

Flow of resources (transportations) Raw material Tier suppliers Manufacturers Distribution Retailers suppliers centers Fig .2 An example of an integrated supply chain

AN INTEGRATED SCM LAYERS OEM’s system integrators first-tier OEM: The original equipment manufacturer e.g. Mercedes, Suzuki, HP, Peugeot. SYSTEM INTEGRATORS: The integrator of the process in most case not physical but are otherwise regarded as the main suppliers to the OEM. SUPPLIERS: The different suppliers (manufacturers) of separate parts. suppliers second-tier Fig.3 Pyramid Structure of an Automotive Industry

THREE BASIC CATEGORICAL LEVELS OF SUPPLY CHAIN ACTIVITIES: • Strategic: Optimization, and partnership with suppliers, distributors, and • customers, creating communication channels for critical information and operational • Improvements. Product design coordination, so that new and existing products can be • optimally integrated into the supply chain, load management Information Technology • infrastructure, to support supply chain operations. Where-to-make and what-to-make • -or-buy decisions. • 2. Tactical: Sourcing contracts and other purchasing decisions. Production decisions including contracting, scheduling, and planning process definition. Inventory decisions, Transportation strategy, and Benchmarking of all operations against competitors as well as implementation of best practices throughout the enterprise. Focus is on customer demand. • 3. Operational: Daily production and distribution planning, including all nodes in the supply chain. Production scheduling for each manufacturing facility in the supply chain (minute by minute). Outbound operations, including all fulfillment activities and transportation to customers. Order promising, accounting for all constraints in the supply chain, including all suppliers, manufacturing facilities, distribution centers, and other customers.

Information Technologies in Supply Chain Management “Information technologies” is an important enabler of effective supply chain management. Much of the current interest in supply chain management is motivated by the possibilities that are introduced by the abundance of data and the savings inherent in sophisticated analysis of these data”. - Simchi-Levi and his colleagues, Below is an illustration of interaction that can only be attain by forward and respond information and data flow. It can be in document form and …… It follows that information technologies in supply chains pursue three goals;

1] Collecting information on each product from production to delivery or purchase point, and providing complete visibility for all parties involved. 2] Accessing any data in the system from a single-point-of-contact, e.g. from a PDA linked to the company information system through a wireless link. 3] Analyzing data, planning activities, and making trade-offs based on information from the entire supply chain. To achieve these activities, information technologies use certain means: – Information technology infrastructure (network, databases. . .); – E-commerce; – supply chain components, which are the various systems directly involved in supply chain planning, i.e., Decision Support Systems (DSS). Concretely, information and decision technologies take the form of: – Enterprise Resource Planning (ERP) ; a class of software systems organizing and managing companies, e.g., PeopleSoft/Oracle, or SSA Global; – E-commerce, and in particular marketplaces, such as Commerce One and Ariba. – Advanced Planning and Scheduling (APS); a class of software for Decision Support System (DSS) in supply chains.

According to Shapiro’s decomposition of information technologies, the first two applications (ERP and e-commerce) belong to “Transactional Information Technologies” because they are concerned with acquiring, processing and Communicating raw data. On the other hand, APS and DSS belong to “Analytical Information Technologies” because they allow analyzing raw data in order to help managers, which is a task at a higher level. In practice, companies first install transactional tools, because analytical tools need them to be fed with raw data. More and more, multi-agent systems are seen as a new technology for improving or replacing technologies used in both transactional and analytical information technologies. We now explain why agent technology seems so promising in the context of supply chains.

HOLONIC SYSTEM (MULTI - AGENT SYSTEM) Stressing the concept of higher decentralized, coordination and control in production system. A holon is an autonomous and cooperative building block of a system (manufacturing or others) for transforming, transporting, storing and or validating information and physical objects. IT has the following as it’s attributes Integration Agility Synchronization Customer-centric Service Information Protection

Motivations For Using Holonic OR Multi-Agent Systems in Supply Chain Management Researchers have already applied agent technology in industry to concurrent engineering, manufacturing enterprise integration, supply chain management, manufacturing planning, scheduling and control and holonic manufacturing systems. Concerning supply chain organized as a network of intelligent agents, it is noted to be made up of heterogeneous (Different types) production subsystems gathered in vast dynamic and virtual coalitions. Intelligent distributed systems, e.g. multi-agent systems, enable increased autonomy of each member in the supply chain. Each partner (or production subsystem) pursues individual goals while satisfying both local and external constraints. Therefore, one or several agents can be used to represent each partner in the supply chain (plant, workshop, etc.). Moreover, the agent paradigm (standard) is a natural metaphor for network organizations.

CHARACTERISTICS OF HOLONIC/MULTI – AGENTS SCM SYSTEMS AUTONOMY: a company carries out tasks by itself without external intervention and has some kind of control over its action and internal state; INTEGRATION:this is an attribute that links all the participants and activities involved in converting raw materials into products and delivering them to consumers at the right time and at the right place. i.e. interacts with other companies e.g. by placing orders for products or services (social ability); SYNCHRONIZATION: synchronizing supplier planning, production planning, logistics planning, and demand planning will provide a comprehensive view of all supply chain activities and enable management to make more informed trade off decisions. AGILITY: SCM systems must be able to process transactions rapidly and accurately. in today's business environment organizations must focus on moving information and products quickly through the entire supply chain, distribution, assembly manufacture and supply. the faster information, and decisions flow through an organization, the quicker it can respond to customer needs and orders. FLEXIBILITY OR REACTIVITY: a company perceives its environment, i.e., the market and the other companies, and responds in a timely fashion to changes that occur in it. In particular, each firm modifies its behaviour and customize its services to meet the needs of distinct customer segments or individual accounts. to adapt to market and competition evolutions. PRO-ACTIVENESS: a company not only simply acts in response to its environment it can also initiate new activities, e.g. launch new products into it.

BASIC TYPES OF HOLON BUILDING BLOCKS IN A HOLONIC MANUFACTURING SYSTEM (HMS) 1) Product holons: A product Holon holds the process and product knowledge to ensure the correct fabrication of the product with sufficient quality. It acts as an information server to the other Holon's in the HMS. A product Holon provides consistent and up-to-date information on the product life-cycle, user requirements, design, and process plan and bill of material. 2) Order holons: An order holon represents a manufacturing order. It is an active entity responsible for performing the work correctly and on time. It explicitly captures all information and information processing of a job (Valckenaers, 1996). 3) Resource holons: A resource Holon consists of a physical part, namely a production resource in the HMS, and of an information processing part that controls the resource. It offers production capacity and functionality to the surrounding Holon's (Wyns, 1996). It holds the methods to allocate the production resources, and the knowledge and procedures to organize, use and control these production resources to drive production. A resource Holon is an abstraction for the production means such as machines, furnaces, conveyors, pipelines, pallets, components, raw materials, tools, tool holders, material storage, personnel, energy, floor space, etc.

Depending on the situation of the environment in which an holonic approach is to be implemented. different types of holon can be created and each holon has a specific role it will be carrying out and cooperating with other holons to achieve the set objective at the same time. Product Holon Order Holon Resource Holon Cell Holon Cell Holon AVG Holon Machine Holon Machine Holon AVG Holon Robot Holon Robot Holon Fig. 4 Types of holons and their relation with each other

CONDITION FOR IMPLEMENTATION Multi-agent systems offer a way to elaborate production systems that are: 1] Decentralized rather than centralized. 2] Emergent rather than planned. 3] Concurrent rather than sequential. It must be used for problems whose characteristics require its capacities. According to Parunak, five characteristics are particularly salient. In fact, agents are best suited for applications that are; 1] Modular 2] Decentralized 3] Changeable 4] Ill-structured 5] Complex

COMPARING MULTI-AGENT SCM WITH CONVENTIONAL SCM To judge relevance for supply chains of autonomous agents, multi-agent systems are identified as biological (ecosystems) and economical (markets) models, whereas traditional approaches are compared with military patterns of hierarchical organization. Table 1 . Agent-based (Holonic) vs. Conventional technologies.

1. Theoretical optima cannot be guaranteed, because there is no global view of the system; 2. Predictions for autonomous agents can usually be made only at the aggregate level; 3. In principle, systems of autonomous agents can become computationally unstable, since, according to System Dynamics, any system is potentially unstable. But on the other hand, the autonomous, agent-based approach has advantages like: 4. Because each agent is close to the point of contact with the real world, the system’s computational state tracks the state of the world very closely. . . 5 . . . . And this tracking is without need for a centralized database. 6. Because overall system behavior emerges from local decisions, the system readjusts itself automatically to environmental noise . . . 7 . . . . Or to the removal or addition of agents; 8. The software for each agent is much shorter and simpler than would be required for a centralized approach, and as a result is easier to write, debug and maintain. 9. Because the system schedules itself as it runs, there is no separate scheduling phase of operation, and thus no need to wait for the scheduler to complete. Moreover, the optima computed by conventional systems may not be realizable in practice, and the more detailed predictions permitted by conventional approaches are often invalidated by the real world.

CASE STUDY For a piston manufacturing company with a dynamic and complex market demand that is very high. How can we utilize Multi-agents system to improve the shop floor in coping and meeting with demand at the lowest adjustments on machine, shortest possible time and easy decision making? DATA MANAGEMENT MAIN DATA BASE MARKET EMPLOYEE DATA SUPPLIER PRODUCTION SCHEDULING TOTAL PRODUCTIVE MAINTENANCE DESIGN AND R&D ANALYSIS DM [DECISION MAKERS] Fig.5 Increase the production capacity by satisfying the aftermath customers. Lower the effects on machines

Raw material supplier Iran Khodro customers 1 MULTI ENTERPRISE LAYER ABC company Saipa customers 2 Piston rings supplier Aftermath customers 3 Diesel piston [factory 1] Sales 1 Car piston [factory 2] Sales 2 ENTERPRISE LAYER Fig.6

SHOP FLOOR LAYER M/C 1 M/C 2 Moulding and initial rough machinery. [work area 1] Final control, grading and packaging. [Work area 3] IN OUT IN OUT Accurate machinery processing. [Work area 2] Queing and surface finishing. [work area 1] AGV AGV Fig.7 CELL LAYER

CURRENT STATE • Piston of up to 3,000,000 are produced. • There is over 3,000 aftermath customer. (i.e. excluding main brand customer which are SAIPA [KIA motor] and IRAN KHODRO [Peugeot motor]). • Over 500 employers. • Location [in the North-west of Iran]. • It is a private own company. • Under pioneer license from MAHLE Brand Germany .

FACTORY AND SHOP FLOOR SYSTEM ORDER Fig.8 PRODUCTION /SCHEDULE DEPT. M 2 M 1 M 3 IN OUT IN OUT IN OUT MAINTENANCE DEPT SALES EVENTS COMMON WITH THIS SYSTEM 1. Rely heavily on the maintenance department 2. The production manager will have to be informed before any major decision are take [from the 2 minute,15 minute and 30 minute stipulated machine breakdown tolerance] 3. The sales have a constraint of giving customer an immediate feed back for meeting an urgent demand. 4. Each machine buffer has a schedule task it must deliver.

PROBLEM STATEMENT A. VARIATIONS IN DEMAND: 1] AFTERMATH [ very high un-predictable demand]: With over 30 different models, quantities demand of different models varies and is high. 2] OEM’s: The issues of customized demand at unplanned time is highly possible and constant. B. HIGH ADJUSTMENTS ON MACHINES: 1] Effects of continuous changing of machine affects machine performance. 2] Risk of quality depreciation as machine specified tolerance and precision level can be affected by adjustments. 3] Human error tend to increase with much adjustments. C. INCREASEMENT IN PRODUCTION [30%]: Available capacity to meet high demand. D. INTEGRATION AND HARMONIZATION: 1] Need for quick and on time accurate information and support on the shop floor.

Fig.9 PROPOSED AGENT TECHNOLOGY MODEL FOR THE SUPPLY SCHAIN HOLON 1 HOLON 2 HOLON 3 HOLON 4 PRODUCTION MANAGER M/C AGENT 1 M/C AGENT 2 M/C AGENT 3 M/C AGENT 4 SUB-HOLON TPM AGENT TPM AGENT TPM AGENT TPM AGENT TPM MANAGER SUB-HOLON BUFFER AGENT BUFFER AGENT BUFFER AGENT BUFFER AGENT SUPPLIER MANAGER SUB-HOLON SALES AGENT SALES AGENT SALES AGENT SALES AGENT SALES MANAGER SUB-HOLON SUB DATA AGENT SUB DATA AGENT SUB DATA AGENT SUB DATA AGENT IT-MANAGER SUB-HOLON Detailed Agents SCM roles Holon and sub-holon

IMPLEMENTATION RE-ADJUSTMENTS CHALLENGES • Training or hiring of personnel to function as a reliable agent. • The same machines can be effectively put into use without increasing production line.

RESOURCE. HOLON 1 M/C COOPERATIVE NEGOTIATION [created any time an order arise] L & T OUTGOING ORDER HOLON RESOURCE. HOLON 2 M/C RESOURCE. HOLON 3 M/C RESOURCE. HOLON 4 M/C SALES INCOMING ORDER HOLON RESOURCE. HOLON 5 M/C CUSTOMER 1 CUSTOMER 2 CUSTOMER 3 Details decision making Holon PRODUCT HOLON [ PD.M ] Overall decision making Holon RESOURCE HOLON [TPM ] SUPPLIER 1 SCM HOLON PRODUCT HOLON [SU- M ] SUPPLIER 2 SCM HOLON PRODUCT HOLON [ I-T . M] Fig.10 ABCAgents SCM domain data flow diagram Design

BENEFITS • Easy decision making that is cooperative and autonomous. • Readjust the change in the system with the least change constraint. • There is consistent up to date information available to all agents in the data pool. • Overall general decision can be made with within the shortest possible time. • High flexibility that meets the satisfying need of the aftermath market/demand. • Transportation issues are addressed as assurance can be given for a prompt response to demand and delivery.

APPLICATION OF VIRTUAL REALITY The ability of Virtual Reality to provide realistic simulations of data, objects and environments, with which users can interact and manipulate in an intuitive and realistic manner is very possible. This has been provided in situations like layout planning and concept creation, operation use, production simulation, operators training. Because of complex structures of Supply Chain and project team major business driver for the use of virtual reality by it’s professionals is to visualize and understand engineering problems and hence reducing risk and uncertainty. It is basically used by companies to address and show their technical competency and expertise. It should be noted that the better a simulation platform corresponds to their application environment, the easier the development process will be.

Before taking a new order from a customer, a simulation model can show when the order will be completed because just taking the new order can affect other orders in the facility. Simulation can be used to augment the tasks of planers and schedulers to run the operation with better efficiency. The aims usually are to test and verify plans, check the material flow routing and control principle, verify the buffer size and location and search for bottlenecks. The data should be real production data if available, or data from similar products or variants in the same product family. This is an interactive analysis, the engineers should return back to cell level studies, if some parameter need more detail study, for example cycle time need to be shorter. Models can be used to plan, design and process day-to-day operation of manufacturing facilities. These “as build” models provide manufacturers with the ability to evaluate the capacity of the system for new orders, unforeseen events such as equipment downtime and changes in operations. Some operations models also provide schedules that manufacturers can use to run their facilities. planning and scheduling systems plans can be complimented.

CONCLUSIONS All these reasons show the relevance to use agents in supply chain management. In other words, thanks to their adaptability, their autonomy and their social ability, agent-based systems is a viable technology for the implementation of communication and decision-making in real-time. Each agent would represent a part of the decision-making process, hence creating a tight network of decision makers, who react in real-time to customer requirements, in opposition to the flood of current processes, which is decided before and after a customers place an order.

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A Reference-Model for Holonic Supply Chain Management Richard Peters and Hermann Többen 1 Mittenwalder Str.51, 10961 Berlin, Germany ,skamtin@web.de 2 TechnischeUniversität Berlin, Franklinstr. 28/29, 10587 Berlin, Germany Hermann.Toebben@sysedv.cs.tu-berlin.de Holonic Manufacturing Systems: Some Scenarios and Issues Martyn Fletcher Agent Oriented Software Ltd, Mill Lane, Cambridge, CB2 1RX, United Kingdom. martyn.fletcher@agent-oriented.co.uk A Framework for Distributed Manufacturing Applications Paulo Leitão, Francisco Restivo 1 Polytechnic Institute of Bragança, Quinta Sta Apolónia, Apartado 134, 5301-857 Bragança; 2 Instituto Desenv. e Inovação Tecnológica, Rua do IDIT, Espargo, 4520-102 Sta Maria da Feira 3 Faculty of Engineering, University of Porto, Rua dos Bragas, 4099 Porto Codex; pleitao@ipb.pt, fjr@fe.up.p Implementing FMEA in a collaborative supply chain environment S. Gary Teng; Engineering Management Program, The University of North Carolina at Charlotte, Charlotte, North Carolina, USA S. Michael Ho; ArvinMeritor, Inc., Troy, Michigan, USA Debra Shumar; Whirlpool Corporation, Benton Harbor, Michigan, USA Paul C. Liu; College of Engineering, Computer Science, and Technology, California State University, Los Angeles, California, USA.

( MULTI-AGENT BASE ) HOLONIC SUPPLY CHAIN MANAGEMENT