James A. Rappold, Ph.D.
Adjunct Instructor of Operations
Research & Articles
Kathryn E. Caggiano, Peter L. Jackson, John A. Muckstadt, James A. Rappold | Operations Research, 2007, 55(2):303-318
In the realm of service parts management, customer relationships are often established through service agreements that extend over months or years. These agreements typically apply to a piece of equipment that the customer has purchased, and they specify the type and timing of service that will be provided. If a customer operates in multiple locations, service agreements may cover several pieces of equipment at several locations. In this paper, we describe a continuous-review inventory model for a multi-item, multiechelon service parts distribution system in which time-based service-level requirements exist. Our goal is to determine base-stock levels for all items at all locations so that the service-level requirements are met at minimum investment. We derive exact time-based fill-rate expressions for each item within its distribution channel, as well as approximate expressions for the gradients of these fill-rate functions. Using these results, we develop an intelligent greedy algorithm that can be used to find near-optimal solutions to large-scale problems quickly, as well as a Lagrangian-based approach that provides both near-optimal solutions and good lower bounds with increased computational effort. We demonstrate the effectiveness and scalability of these algorithms on three example problems.
https://doi.org/10.1287/opre.1060.0345
John A. Muckstadt, David H. Murray, James A. Rappold, Dwight E. Collins | Information Systems Frontiers: Special Issue on Supply Chain Management, 2001, 3(4):427-453
Over the past decade, firms have adopted supply chain management as a critical element of their corporate strategies. Despite these efforts, it is our observation that many firms do not realize the anticipated benefits of constructing collaborative operating relationships with supply chain partners. Our purpose in this paper is to establish a set of guiding principles for the effective design and execution of supply chain systems. These principles suggest why, what, and how collaborative relationships should be constructed.
James A. Rappold, Keenan D. Yoho | International Journal of Production Economics, 2014, 156:146-158
In the process industries, specialized equipment and production processes often necessitate the manufacture of products in a pre-determined sequence to minimize changeover time and to simplify scheduling complexity; these types of schedules are referred to as pure rotation schedules, or product wheels, where the circumference of the wheel is the production cycle length. In these industries changeover times between the production of individual products can consume considerable time as well as raw materials and it is therefore often desirable to stabilize the production cycles in order to minimize unplanned changeovers as well as quote accurate lead times to customers. Materials requirements planning (MRP) systems are often used to plan and coordinate production and supply resources with demand in these environments. Central to the effectiveness of the MRP system is the dependability of the lead time parameters. In this paper, we introduce an optimization model to determine safety stock levels that minimize long run expected costs where a stable, cyclic schedule is used. Our model may be used strategically to assess inventory investment requirements as a function of capacity investment, product mix, production technology, demand volatility, and customer service levels. It may be used tactically to optimize item-level planning parameters such as lot size, safety stock and lead time in an MRP system and to support sales and operations planning (S&OP) processes where knowing the future costs associated with current decisions is highly desirable.