Optimization of a multi-objective lean assembly problem with reconfigurable machine cells

Abstract

Manufacturing sector is regularly facing the challenges caused due to high market dynamics and mass customization. Traditionally designed machine cells fail to address this issue due to lack of flexibility in capacity and functionality. However, the benefits of cell based production can be achieved by changing the machines involved and the design of cells. This paper presents a hybrid model of machine cells comprising of reconfigurable machine tools (RMTs) that are acting as part feeders for a lean assembly line of discrete products. The strategies of lean manufacturing to maintain the Takt time and synchronized one-piece-flow are considered in the model. A multi-objective optimization problem is formulated and solved to minimize the inter-cellular part movement, the error for Takt time among machine cells and the total reconfiguration time of the RMTs using NSGA-II metaheuristic. A numerical case example for the model is solved using MATLAB© and illustrated along with computational steps and Pareto optimal solutions.

Productivity improvement by application of simulation and lean approaches in an multimodel assembly line

“…Data analytics in simulation is used with the Internet of Things (IoT) to address bottleneck problems while adhering to the LM principle. Pattanaik and Kant 20 emphasized how the advantages of cell-based manufacturing can be realized by modifying the machinery involved and the cell architecture. This study describes a hybrid concept of machine cells made up of reconfigurable machine tools (RMTs) that serve as component feeders for a lean assembly line.…”