Grace Y. Lin

INTEGRATED SHOP FLOOR CONTROL USING AUTONOMOUS AGENTS

In this paper, we present a generic framework for controlling the work flow in computer controlled manufacturing systems. Based on a market-like model and a combination of objective and price mechanism, the framework allows heterogeneous job objectives, admits job priorities, recognizes multiple resources types, and allows multiple step negotiation between parts and resources. The framework is designed to accommodate frequent changes in the environment such as machine failures, tool shortages, and process requirement variations. An object-oriented simulation system is built to demonstrate the flexibility and effectiveness of die proposed framework. The results show that the proposed framework provides a foundation for highly adaptive, real time shop floor control.

A Supply Network Model with Base-Stock Control and Service Requirements

We develop a supply network model that takes as input the bill of materials, the (nominal) lead times, the demand and cost data, and the required customer service levels. In return, the model generates the base-stock level at each store--the stocking location for a part or an end-product, so as to minimize the overall inventory capital throughout the network and to guarantee the customer service requirements. The key ingredient of the model is a detailed, albeit approximate, analysis of theactual lead times at each store and the associated demand over such lead times, along with a characterization of the operation at each store via an inventory-queue model. The gradients are derived in explicit forms, and a conjugate gradient routine is used to search for the optimal solution. Several numerical examples are presented to validate the model and to illustrate its various features.

Inventory-Service Optimization in Configure-to-Order Systems

This study is motivated by a process-reengineering problem in personal computer (PC) manufacturing, i.e., to move from a build-to-stock operation that is centered around end-product inventory towards a configure-to-order (CTO) operation that eliminates endproduct inventory. In fact, CTO has made irrelevant the notion of preconfigured machine types and focuses instead on maintaining the right amount of inventory at the components. CTO appears to be the ideal operational model that provides both mass customization and a quick response time to order fulfillment. To quantify the inventory-service trade-off in the CTO environment, we develop a nonlinear optimization model with multiple constraints, reflecting the service levels offered to different market segments. To solve the optimization problem, we develop an exact algorithm for the important case of demand in each market segment having (at least) one unique component, and a greedy heuristic for the general (nonunique component) case. Furthermore, we show how to use sensitivity analysis, along with simulation, to fine-tune the solutions. The performance of the model and the solution approach is examined by extensive numerical studies on realistic problem data. We present the major findings in applying our model to study the inventory-service impacts in the reengineering of a PC manufacturing process.

Experience using the IBM supply chain simulator

The IBM Supply Chain Simulator (SCS) is a software tool that can help a company or a group of companies make strategic business decisions about the design and operation of its supply chain. SCS and its predecessors were originally developed by IBM Research to improve IBMs internal supply chains. The tool has played an important role in the resurgence of IBM over the last six years (1992-8). In 1997 the IBM Industry Solution Units began using the tool to help its clients improve their supply chains. After about a year of business, successful engagements have been completed in a variety of geographies and business segments. SCS deploys a mix of simulation and optimization functions to model and analyze supply chain issues such as site location, replenishment policies, manufacturing policies, transportation policies, stocking levels, lead times, and customer service. The paper reviews the capabilities of SCS and presents experience from practical studies.

Extended-Enterprise Supply-Chain Management at IBM Personal Systems Group and Other Divisions

In 1994, IBM began to reengineer its global supply chain. It wanted to achieve quick responsiveness to customers with minimal inventory. To support this effort, we developed an extended-enterprise supply-chain analysis tool, the Asset Management Tool (AMT). AMT integrates graphical process modeling, analytical performance optimization, simulation, activity-based costing, and enterprise database connectivity into a system that allows quantitative analysis of extended supply chains. IBM has used AMT to study such issues as inventory budgets, turnover objectives, customer-service targets, and new-product introductions. We have implemented it at a number of IBM business units and their channel partners. AMT benefits include over

Applications of flexible pricing in business-to-business electronic commerce

750 million in material costs and price-protection expenses saved in 1998.

Effectiveness of flexible routing control

The increasingly dynamic nature of business-to-business electronic commerce has produced a recent shift away from fixed pricing and toward flexible pricing. Flexible pricing, as defined here, includes both differential pricing, in which different buyers may receive different prices based on expected valuations, and dynamic-pricing mechanisms, such as auctions, where prices and conditions are based on bids by market participants. In this paper we survey ongoing work in flexible pricing in the context of the supply chain, including revenue management, procurement, and supply-chain coordination. We review negotiation mechanisms for procurement, including optimization approaches to the evaluation of complex, multidimensional bids. We also discuss several applications of flexible pricing on the sell side, including pricing strategies for response to requests for quotes, dynamic pricing in a reverse logistics application, and pricing in the emerging area of hosted applications services. We conclude with a discussion of future research directions in this rapidly growing area.

Autonomous control for open manufacturing systems

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available.To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived.The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.

The Stochastic Knapsack Revisited: Switch-Over Policies and Dynamic Pricing

The manufacturing environment is undergoing fundamental changes. Transfer lines, numerical control, computerized numerical control machines, automated material handling systems, automatic tool change systems, computer integrated manufacturing (CIM), and flexible manufacturing systems (FMS) have come into being. Recently, the intelligent manufacturing system (Solberg et al., 1985) concept was raised in the hope that it will increase product quality and productivity and achieve a high degree of customization. We can expect to see these trends continue because they are driven by competitive forces. It is economically advantageous for a company to adopt any technology that works effectively in the direction of greater integration, greater flexibility and greater responsibility. However, the manufacturing environment is a large, complex system of interrelated activities. Success of these systems depends on the development of computer-based decision making and efficient control structures to manage its activities.

Product Hardware Complexity and Its Impact on Inventory and Customer On-Time Delivery

The stochastic knapsack has been used as a model in wide-ranging applications from dynamic resource allocation to admission control in telecommunication. In recent years, a variation of the model has become a basic tool in studying problems that arise in revenue management and dynamic/flexible pricing, and it is in this context that our study is undertaken. Based on a dynamic programming formulation and associated properties of the value function, we study in this paper a class of control that we call switch-over policies---start by accepting only orders of the highest price, and switch to including lower prices as time goes by, with the switch-over times optimally decided via convex programming. We establish the asymptotic optimality of the switch-over policy, and develop pricing models based on this policy to optimize the price reductions over the decision horizon.