A Decision Support System for Pre-Cast Concrete Manufacturing Planning: An Innovative Crew Allocation Optimiser

The high cost of skilled labour in the precast concrete industry and the dynamic nature of the production processes have encouraged senior managers in the industry to develop a more intelligent and optimal allocation strategies. In this paper, the Genetic Algorithm (GA)-based simulation optimisation approach is used for the optimal allocation of different crews of workers on different precast concrete production processes. A Precast-Component manufacturing simulation model is integrated to GA-based optimisation model to simulate the physical processes that are involved in the manufacturing system and to optimise the allocation of labour crews. The proposed approach determines the optimal or near optimal allocation of crews for the processes involved within the precast manufacturing system., This should eventually lead to maximum utilisation of the set of skilled workers involved in the allocated crew and subsequently minimise the total labour costs.
The paper discusses a simulation system dubbed “SIM_Crew” that was developed during this study. This simulation model is developed as a test bench for the proposed intelligent allocation system. GA is used to guide simulation towards the best course of action; chromosome is designed well to involve all the decision variables. An innovative selection procedure is developed in order to guarantee the best selection of chromosomes. The results showed that efficient utilization of skilled labour had a substantial impact on reducing the throughput time, minimising labour costs, idle times and maximising the skilled workers utilisation.