Revenue Management in Order‐Driven Production Systems

Abstract

This article investigates the effectiveness of a tactical demand-capacity management policy to guide operational decisions in order-driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first-come-first-served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order-processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order-processing approach.

Revenue Management in Make-To-Order Manufacturing: Case Study of Capacity Control at ThyssenKrupp VDM

“…Therefore, adapting available capacity to short-term fluctuations of demand is not practical (Harris and Pinder 1995). Further, Barut and Sridharan (2005) observe that quickly adding capacity could lead to a glut and seriously jeopardize the health of a company in the long term. The requirement of a capacity shortage is interconnected with fixed capacity.…”

“…Starting in the mid-90's, initial works of Balakrishnan, Sridharan, and Patterson (1996), Harris and Pinder (1995) and Patterson, Balakrishnan, and Sridharan (1997) investigate the application of RM methods to manufacturing environments in general. Models of capacity control in m-t-o environments, specifically, are later presented by Barut and Sridharan (2005), Defregger and Kuhn (2007), Gallien, Le Tallec, and Schoenmeyr (2004), Gupta and Wang (2004) and Jalora (2006), all considering the sequential order acceptance for multiple offered products with exogenous delivery dates with respect to expected demand. Spengler, Rehkopf, and Volling (2007) extend the above list by additionally providing a detailed description of an observed production structure.…”

Revenue Management in an Assemble-to-Order Production System

“…Their decisions are based on bid prices, which are computed via a multi-dimensional knapsack problem formulation. Barut and Sridharan (2005) develop a heuristic approach to compute the capacity contingents for several customer classes to decide which orders to accept in an orderdriven production system, but they do not model raw material requirements. Gallien et al (2004) describe a model for admission control in a single server queue with preemption allowed at no cost.…”

Revenue management for manufacturing companies

“…Only orders whose contribution margins exceed the optimal lower bounds are accepted. Barut and Sridharan (2005) propose a heuristic procedure based on a decision tree analysis in order to determine amounts of consumable capacity for each order class that can be used to accept orders of this class.…”