Manufacturing Planning and Control Systems

Willem Hendrik Maria Zijm, Alberto Regattieri

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

3 Citations (Scopus)


In this chapter, we discuss essentials of the best-known manufacturing planning and control systems. Each of these systems has its merits but each one also requires a number of conditions to be fulfilled in order to perform near-optimally, often without being explicit about these conditions. The focus of this chapter will be on discrete manufacturing planning and control with limited attention to process industries. We begin the discussion at a basic level with the most elementary result of efficiency-driven production, the Economic Production Quantity, and an extension to non-stationary deterministic demand. Next, we continue with an introduction to Materials Requirements Planning (MRP) and Manufacturing Resources Planning (MRP II), followed by a discussion of capacity oriented Hierarchical Production Planning (HPP). On a more advanced level, we introduce an entirely different approach based on the adoption of the Just-in-Time (JIT) and Lean Manufacturing (LM) philosophies. JIT and LM are more than just other planning models; they propose an entirely different approach to organizing manufacturing and assembly processes. A case study on the Toyota production system helps to understand key concepts of Lean Manufacturing. We continue with the concepts of Workload Control and the Theory of Constraints, which can be seen as means to keep internal lead times stable and hence predictable. Finally, we provide a glimpse on state-of-the-art and future developments, with a focus on digital and cloud manufacturing.
Original languageEnglish
Title of host publicationOperations, Logistics and Supply Chain Management
EditorsHenk Zijm, Matthias Klumpp, Alberto Regattieri, Sunderesh Heragu
ISBN (Electronic)978-3-319-92447-2
ISBN (Print)978-3-319-92446-5
Publication statusPublished - 2019

Publication series

NameLecture notes in logistics
ISSN (Electronic)2194-8925


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