Variable takt time groups and workload equilibrium

Abstract

Natural disasters, pandemics, and political nationalism force companies toward more responsive, flexible, and resilient assembly systems. For manufacturers, adaptability of the assembly process and local production ensure short product lead times even during supply chain disruptions. Yet one downside of regional production is that fixed takt time assembly lines become overburdened, especially when customisation is unlimited. In this context, variable takt time groups (VTGs) are a major competitive lever. We introduce the notion of a workload equilibrium balancing overload and underutilization. This preliminary stage of the assembly line balancing and sequencing problem significantly reduces the planning effort. Moreover, we present a model for minimising (i) the number of VTGs for a given maximum operator drift per unit or (ii) the maximum operator drift per unit for a given number of VTGs. We solve these dynamic problems by developing a heuristic approach: the variable takt time groups algorithm (VTGA). In our analysis of three real-world data sets from two German manufacturers—Fendt and Rolls-Royce Power Systems—we benchmark the VTGA against existing takt times. We find that VTGs result in higher labour efficiency than a fixed takt time and that the VTGs segmentation level plays an important role in reducing operator inefficiencies.

KEYWORDS:

• Manufacturing
• mixed-model assembly line
• variable takt times
• variable takt time groups
• workload equilibrium

Acknowledgments

The authors thank Herbert Dengler of Rolls-Royce Power Systems for sharing his knowledge about Rolls-Royce Power Systems’ supply chain structure and providing the data of the Rolls-Royce Power Systems’ engine assembly line in Friedrichshafen, Germany.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 To ensure confidentiality, all assembly times in this document are scaled to their weighted average takt time—a transformation that preserves their relative values.

Additional information

Notes on contributors

Tobias Mönch

Tobias Mönch holds a Ph.D. in Operations form the WHU – Otto Beisheim School of Management in Vallendar, Germany. After his Ph.D. he was invited to join the Operations, Information and Decision Department of The Wharton School, University of Pennsylvania, USA, as postdoctoral researcher. His research focuses, among others, on flexible manufacturing systems, mixed-model assembly line optimization, and inventory design mechanism.

Arnd Huchzermeier

Arnd Huchzermeier is Chaired Professor of Production Management at WHU’s Otto Beisheim School of Management in Vallendar, Germany. He holds a Ph.D. degree in Decision Sciences from The Wharton School of the University of Pennsylvania, USA. He is co-founder of the prestigious Industrial Excellence Award in Europe. His research interests include, among others, Management-Quality for Industrial Excellence, Global Supply Chain Risk Management and Operations Management Interface to Marketing and to Finance.

Peter Bebersdorf

Peter Bebersdorf is Director Manufacturing Tractor Fendt at the AGCO site in Marktoberdorf, Germany. AGCO is a global leader indesigning, manufacturing and distribution of smart solutions for sustainable agriculture. He holds a MBA in International Management Consulting from the University of Applied Science Ludwigshafen, Germany, and a BSc in Electrical Engineering from the Baden-Württemberg Cooperative State University Mannheim, Germany. His research interest focus on managerial implications and design of mixed-model assembly systems, especially variable takt time systems.