The application of Activity Based Costing (ABC) approach to select the set-machine that is used in the production of Flexible Manufacture System (FMS) based on technical and economical criteria can be useful for producers to design FMS by considering the minimum production cost. In the other hand, Heuristic Search is known to have a short searching time. Algorithm Heuristic that using ABC approach as the weight in finding the solution to shorten the equipment selection time during the design / redesign process of the FMS in less than exponential time was designed in this research. The increasing speed is useful because with the faster time in design / redesign process, therefore the flexibility level of part variety that can be processed will become better Theoretical and empirical analysis in Algorithm Heuristic shows that time searching to get appropriate set of equipment is not too long, so that we can assume that the designed Algorithm Heuristic can be implemented in the real world. By comparing the empirical result of Algorithm Heuristic to the Algorithm Exhaustive, we can also assume that Algorithm Heuristic that using ABC method as the weight for finding solution can optimise the equipment selection problem of FMS based on economical criteria too.

The decisions to choose appropriate tools for solving industrial problems are not just tools that achieve optimal solution only but it should consider computation time too. One of industrial problems that still difficult to achieve both criteria is scheduling problem. This paper discuss comparison between mixed integer programming which result optimal solution and heuristic method to solve job shop scheduling problem with separable sequence-dependent setup. The problems are generated and the result shows that the heuristic methods still cannot satisfy optimal solution.

The paper describes a dynamic variant of the traditional ABC storage policy. The variant is to be used in manual order picking warehouses where SKUs experience a rather unstable demand. Its objective is to reduce the order picking time. It mainly consists in shifting items between the storage areas A, B and C according to the way their daily number of order lines changes. A few case studies based on computer simulations have shown that this variant can yield interesting time savings if its parameters are chosen with care. One of those case studies is presented in this paper. Because of the pioneering nature of this variant, some ideas for further research are also sketched.