Minimise loom changeover time at MONN

Abstract

MONN is a manufacturer of premium quality and custom woven Axminster carpeting. The process of making a custom woven Axminster carpet involves many processes but the weaving process o ered room for improvement in the throughput and changeover time of the 5 looms, which weave the carpets. It was identi ed that the looms created a bottleneck in the factory making any improvement in loom changeover time valuable. The processes and methods in place when setting up a loom for a new job were uner- gonomic and slow. Using multiple literature sources that looked into facilities planning and the ergonomics of preparing the looms, new methods improving ergonomics and speed were devel- oped. Two new scenarios were developed which could lead to possible improvements over the current system. In order to assign a monetary value to the di erent scenarios, AnyLogic was used as a simulation tool to model the di erent scenarios. AnyLogic is a simulation program that by utilising the concept of discrete and agent based modelling provides a platform to simulate a process with accuracy. The current processes and systems MONN uses was simulated providing a foundation for the new scenarios for and benchmark to which they can be compared to. To ensure that the base model was realistic; validation and calibration experiments were conducted. Once the based model was completed, the new scenarios could be developed using simulation. Two scenarios were developed where changes in the material handling systems and improve- ments in general ergonomics were made. An additional scenario was added where sta were relocated to new positions to further improve performance. The results of the scenarios' simulation models were documented, and the monetary values of the simulations were assessed to determine the feasibility. It was found that all proposed sce- narios were an improvement over the current system and would that they would pay themselves in 5{8 years contributing R500 000 { R1 350 000 a year to pay themselves o , depending on the scenario.