Design of real-time manifacturing planning and control system via information sharing

Spread of digital technology in every slice of life provides that the needs have been addressed within the individual scope and also it increases competition to the level of both individual solution and personal production. Accordingly, the development of production systems continues to enhance for managing the diversity. One of the milestones of this development and transformation process is mass customization called the fourth industrial revolution, Industry4.0. Enterprises should be able to overcome with the diversity and variability due to diversity in the production environment in order to keep pace with Industry 4.0. The methods improved in attempt to cope with variability in the production, are keeping inventory or working with time tolerances. In this case, efficiency decreases and overhead cost per unit increases in. A novel production planning approach and a model which is eliminated from negative aspect of conventional methods has been proposed, in this study. The proposed model is based on a time parameter less affected by the variances rather than the quantity in order to avoid being influenced by the changes. The remaining time to stock-out instead of inventory level is taken into account in this model, and prioritization is proceed according to the time remaining to complete the production and due date in the scheduling process. Thus, the model based on a time parameter is a real-time model. Being real-time provides, the model, to be affected from variances less than quantity based methods. It is presented that the real-time model is not affected by the variances in the manufacturing environment, and provides completing manufacturing process with less delays by using no safety stock. Besides, an algorithm having O(n) time complexity provides this result. Though the application of model is easy as algorithmically, the model, being real-time, requires the live inventory and production data within the determined time cycle. Because the data can be gained by the cyber-physical technologies of Industry 4.0, real-time model can be applied to modern production systems. The contribution of this model to production systems is that the model assimilates manufacturing systems as pull or push system at the same time. Selecting the productive strategy dynamically enables the decrease of more than 90% inventory cost.