Development of a Methodology for the Analysis and Evaluation of Alternative Actions in Disruption Management in Production

Ben Luetkehoff,Volker Stich,Felix Steinlein,Moritz Schroeter

doi:10.1007/978-3-030-28464-0_13

Abstract

Due to Digital Transformation, also called Industry 4.0 or the Industrial Internet of Things, the barrier for implementing data collecting technology on the shop floor has decreased dramatically in the past years – leading to an increasingly growing amount of data from a multitude of IT systems in production companies worldwide. Despite that, the production controller still relies heavily on intrinsic knowledge and intuition for the management of disruptions in production. Thanks to advances in the fields of production control and artificial intelligence, potentials for the collected data for disruption management arise. However, in order to transform data into usable information and allow drawing conclusions for disruption management in production, the relevant data-objects, disturbances and alternative actions must be known. Thus, the decision-making can be supported, reducing the decision latency and increasing benefit of alternative actions. Therefore, the goal of this paper is to discuss the prerequisites necessary to perform a data based disruption management and the methodology itself, serving as an approach to allow companies to build a data basis, classify disruptions and alternative actions in order to improve decision making in the future.

Highlights

Offering customer specific products defines small and medium enterprises (SMEs), especially mechanical and plant engineering companies
While solutions – even automated ones – exist in the field of detailed planning, the production controller is usually left unsupported in many areas when it comes to disruption management [4]
While many aspects of production have already been facilitated by this digital transformation, the disturbance management remains unsupported and mostly based on implicit knowledge and intuition of the worker

Summary

Introduction

Offering customer specific products defines small and medium enterprises (SMEs), especially mechanical and plant engineering companies. This, combined with increasing product varieties and deceasing product lifecycles, leads to highly complex production processes, which in turn lead to an increasing amount of potential disturbances [1, 2] These company-internal or -external disturbances are to blame for disruptions and their effect on, for example, delivery dates. While solutions – even automated ones – exist in the field of detailed planning, the production controller is usually left unsupported in many areas when it comes to disruption management [4]. This makes the job of a production controller increasingly difficult. The methodology is part of the research project “iProd” with the goal of developing a collaborative platform [5, 6]

Objectives

Methods

Conclusion