Workload-dependent capacity control in production-to-order systems

Abstract

The development of job intermediation and the increasing use of the Internet allow companies to carry out ever quicker capacity changes. In many cases, capacity can be adapted rapidly to the actual workload, which is especially important in production-to-order systems, where inventory cannot be used as a buffer for demand variation. We introduce a set of Markov chain models to represent workload-dependent capacity control policies. We present two analytical approaches to evaluate the policies' due-date performance based on stationary analysis. One provides an explicit expression of throughput time distribution, the other is a fixed-point iteration method that calculates the moments of the throughput time. We compare due-date performance, capacity, capacity switching, and lost sales costs to select optimal policies. We also give insight into which situations a workload-dependent policy is beneficial to introduce. Our results can be used by manufacturing and service industries when establishing a static policy for dynamic capacity planning.

Tactical capacity planning in a real-world ETO industry case: An action research

“…Ideally, this flexibility should support the planner in making a trade-off between the expected delivery performance and the expected costs (Hans et al, 2007). In general, the basic capacity flexibility options are overtime, hiring personnel, temporary labour, subcontracting and changing inventory levels (Mincsovics and Dellaert, 2009;Jamalnia and Feili, 2013;Lingitz et al, 2013).…”

INCAP – applying short-term flexibility to control inventories

“…• Workload-dependent capacity control: Mincsovics and Dellaert (2009) investigate a workload-dependent capacity control for make/engineer-to-order-settings; a similar method can be traced back to Tijms and van der Schouten (1978). The workload-dependent capacity planning policy is defined by two switching points:…”

State probabilities for an M/M/1 queuing system with two capacity levels

“…On the other hand the capacity can be adjusted to the fluctuations of the customer demand (Altendorfer et al 2014;Bradley and Glynn 2002;Defregger and Kuhn 2006;Kok 2000;Li et al 2009;Mincsovics and Dellaert 2009;van Mieghem and Rudi 2002). The methods discussed in this paper are based on capacity adjustment literature.…”