Incorporating physical demand criteria into assembly line balancing

Brian J. Carnahan, Bryan A. Norman, Mark S. Redfern

IIE Transactions · 2001 · 93 citations · 28 references

Concepts

TL;DR

Many assembly line balancing algorithms consider only task precedence and duration, ignoring physical demands that can lead to musculoskeletal disorders. The study developed three line‑balancing heuristics that incorporate physical demand criteria to find assembly line balances that consider both time and physical demands. The authors created a ranking heuristic, a combinatorial genetic algorithm, and a problem space genetic algorithm, and tested each on 100 assembly line balancing problems. Incorporating physical demands altered assembly line configuration, with the problem space genetic algorithm best minimizing cycle time and physical workload, offering benefits for manufacturing environments.

Abstract

Many assembly line balancing algorithms consider only task precedence and duration when minimizing cycle time. However, disregarding the physical demands of these tasks may contribute to the development of work-related musculoskeletal disorders in the assembly line workers. Three line balancing heuristics that incorporate physical demand criteria were developed to solve the problem of finding assembly line balances that consider both the time and physical demands of the assembly tasks: a ranking heuristic, a combinatorial genetic algorithm, and a problem space genetic algorithm. Each heuristic was tested using 100 assembly line balancing problems. Incorporating physical demands using these algorithms does impact the assembly line configuration. Results indicated that the problem space genetic algorithm was the most adept at finding line balances that minimized cycle time and physical workload placed upon participants. Benefits of using this approach in manufacturing environments are discussed.

References

28