Not lean by default: Exploring practices, their design, and underlying mechanisms driving performance

Lean manufacturing is widely adopted by manufacturers in an effort to improve quality, reduce throughput times, and reduce cost. Nevertheless, the literature on the performance implications of lean manufacturing is inconclusive. Manufacturers not only often implement different manufacturing practices but do so in completely different ways. Therefore, it is important to study how practices used to implement lean manufacturing jointly affect performance and explore how their design and underlying mechanisms drive performance. This dissertation addresses these two issues, employing different methodologies.
The first study addresses the relation between quality management practices and performance and shows by means of a combination of meta-analytical and structural equation modeling techniques that quality management practices jointly, rather than independently, affect performance. The two other studies address the design of a specific lean manufacturing practice, namely pull production. The second study shows by means of discrete-event simulation how the design of pull production systems enables improved throughput time performance by facilitating workload balancing. The third study shows by means of an experiment how the design of pull production systems influences motivation gains and losses of individuals within production systems. Together, these studies demonstrate the importance of studying lean manufacturing practices, their design, and the underlying mechanisms that drive performance As such, these studies direct manufacturers to take a holistic yet customized approach to lean manufacturing.