Markus Ettl

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.

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

A technical framework for sense-and-respond business management

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

Simulating distribution of emergency relief supplies for disaster response operations

In this paper we present a technical framework that supports sense and respond (SaR), the approach that enables an enterprise to adapt to a rapidly changing business environment. To implement the SaR approach, an enterprise proactively monitors trends and uses effective decision-support tools to help it act in a timely manner. We describe two pilot projects in which we implemented SaR prototypes and applied them to solve business problems. In the first pilot project we helped the IBM Microelectronics Division deploy an automated inventory management system based on our inventory optimization model. In the second pilot project, we helped the IBM Personal Computing Division deploy a SaR system in support of demand/supply conditioning. One of the components of this SaR system is an order trend model that provides early warning of constraints and excesses in the supply chain and helps make demand/supply conditioning more effective. Early results from these projects are encouraging and show that significant gains in profitability are possible.

Sojourn Time and Waiting Time Distributions for M/GI/1 Queues with Preemption-Distance Priorities

In the event of disasters such as hurricanes, earthquakes and terrorism, emergency relief supplies need be distributed to disaster victims in timely manner to protect the health and lives of the victims. We develop a modeling framework for disaster response where the supply chain of relief supplies and distribution operations are simulated, and analytics for the optimal transportation of relief supplies to various POD (Points of Distribution) are tested. Our simulation model of disaster response includes modeling the supply chain of relief supplies, distribution operations at PODs, dynamics of demand, and progression of disaster. Our analytics optimize the dispatch of relief supplies to PODs and cross-leveling among PODs. Their effectiveness is estimated by the simulation model. The model can evaluate a wide range of disaster scenarios, assess existing disaster response plans and policies, and identify better approaches for government agencies and first responders to prepare for and respond to disasters.

Designing Flexible Supply Chain Contracts with Options

Scheduling strategies for real-time systems often employ semipreemptive priorities, allowing for a deadline enforcement by preemptive priorities while avoiding the overhead of unnecessary interrupts. A variety of these strategies can be described by preemption-distance priorities in a straightforward and flexible fashion. A preemption-distance is a globally assigned positive integer number. An arriving task must exceed the priority of the task being served by at least the preemption-distance to cause a preemption. We derive the Laplace-Stieltjes transforms of the marginal waiting and sojourn time distributions for each task class in M/GI/1 single-server queues with preemption-distance priorities. The solutions generalize results for the classical M/GI/1 preemptive and nonpreemptive priority queues and cover a variety of priority systems working under different service policies. The basic derivations are straightforward and lead to solutions which are easy to interpret with respect to the influence of the ...

Managing product availability in an assemble-to-order supply chain with multiple customer segments

In many industries, original equipment manufacturers (OEMs) are focusing on a limited range of core competencies and choosing to procure nonessential goods or services from suppliers and third-party service providers. The result is a highly decentralized supply chain, where each supply chain partner attempts to maximize its own profit objective, based on its own private information. Given the uncertainties present in both procurement decisions, often manifested in substantial forecast errors in materials or service requirements, the execution of supply agreements can have a significant impact on the firm’s operational and financial performance. Supply chain contracts are contractual agreements governing the pricing and exchange of goods or services between independent partners in a supply chain. Properly designed supply contracts are an effective means to share the demand and supply risk and better coordinate such decentralized supply chains. It is widely recognized that suppliers and buyers can benefit from coordination and thereby improve the overall performance of the supply chain as a whole, as well as, frequently the performance of each individual party.

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

In this article, we propose a novel availability management process called Available-to-Sell (ATS) that incorporates demand shaping and profitable demand response to drive better supply chain efficiency. The proposed process aims at finding marketable product alternatives in a quest to maintain a financially viable and profitable product portfolio, and to avoid costly inventory overages and shortages. The process is directly supported by a mathematical optimization model that enables on demand up-selling, alternative-selling and down-selling to better integrate the supply chain horizontally, connecting the interaction of customers, business partners and sales teams to procurement and manufacturing capabilities of a firm. We outline the business requirements for incorporating such a process into supply chain operations, and highlight the advantages of ATS through simulations with realistic production data in a computer manufacturing environment. The models featured in this paper have contributed to substantial business improvements in industry-size supply chains, including over

Utilizing simulation to evaluate business decisions in sense-and-respond systems

100M of inventory reduction in IBM’s server computer supply chain.