Aligning the Production Planning and Control Process with Prognostics and Health Management

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Nov 24, 2021
Kevin Wesendrup Bernd Hellingrath

Abstract

Production planning and control (PPC) is the heart of any manufacturing company and entails tasks such as resource planning, sequencing, or capacity control. While an increas-ing complexity within production makes it difficult to deter-mine the best production plan, the advances in PHM and the emergence of predictive maintenance also offer new oppor-tunities to optimize PPC. While there is much research on PHM and PPC, little has been done to align both disciplines. Through post-prognostics decision-making, different PPC decisions, such as continuing the production, shutting down a machine, or reducing its workload, can be elevated by a re-maining useful life (RUL) estimation. However, it is unclear how exactly this prognostics information can be exploited and how processes, organization, and technology must be aligned to attain a more efficient and flexible production. Fur-ther, PHM has long been implemented beyond research, but it is unknown whether and how practitioners intertwine it with their PPC. This work aims to analyze how processual, organizational, and technological changes through PHM can lead to advanced PPC. This goal is attained by means of a multivocal literature review (MLR) in which scientific PPC and PHM literature and standards are analyzed, and an aligned PPC process proposed. The findings are juxtaposed with grey literature, revealing fits and gaps between research and practice, and a research agenda is presented.

How to Cite

Wesendrup, K., & Hellingrath, B. (2021). Aligning the Production Planning and Control Process with Prognostics and Health Management. Annual Conference of the PHM Society, 13(1). https://doi.org/10.36001/phmconf.2021.v13i1.2990
Abstract 716 | PDF Downloads 620

##plugins.themes.bootstrap3.article.details##

Keywords

post-prognostics, production planning, production control, decision-making, literature review

Section
Technical Research Papers