Lean-Safety Six-Sigma

The heijunka tracking matrix has a direct impact on turnover times of the inventory to revamp existing orders as well as new systems. The tracking problem is interested in rearranging the location of VSM (e.g., items, pallets and Aisles) in a grouping of cellular aspect which increase performance level. One of the successful recommendations used in this context is traveler salesman technique but with periodically update (i.e., Dynamic Gemba), it may be need reformulation. Its importance is the capture of work, information, and material (WIP, setup time, process time/unit, error rates, idle time, etc) which is essential in quantifying and determining waste in terms of cost, delivery time and transportation frequency. This paper is interest in review the dynamic Gemba model to improve the inventory handling via applying the genetic algorithm. The proposed heuristic procedures are interested in arrange the inventory in minimum time and maximum flexibility in preparing the different orders. The Gemba tasks displayed via (Gemba KPI board) which contain cost and time information (NNVA: preparing, VA: traveling and NNVA: unloading). The optimized cost and time analysis after reducing NNVA time and total VA time were sent to the central heijunka matrix. The methodology which includes elimination movements and motion wastes are LSS aim to increase the ability of prepare a lot of service in minimum time.