Enhance VSM tool via integrating AHP and ARIMA in scheduling problem

The diversity of demand and specifications has become a significant and mandatory for competitiveness issue among the factories to satisfy the customers in jerky demand case, it is originally a scheduling challenge. The main problem is facing the loss of factories their credibility in determining exact delivery time, due to its reliance on elements of the production chain, which begins with the selection of suppliers and then schedule human activities "NNVA", then machining time "VA". Customer satisfaction alerts these factories to quickly meet customers' orders (i.e., quantity, quality, price and delivery time) via selecting appropriate supplier and schedule a NNVA and VA activities resulted due to human intervenes. The AHP works on real data based on factor's weight (i.e., courtesy's suspicion) stands out preferable alternative, but if the selection depends on dynamic decision for future unknown, at this time the hybrid should be thrown. This paper proposed hybrid AHP and ARIMA as a neutral lean selection tongue. AHP fed by ARIMA's results to enhance the selection and achieving continuity via reducing a waste especially a lead time and scheduling setup time. The results of proposed methodology have been reviewed by VSM.