Sustainable Production Planning Using the Ranked Positional Weight Technique and Bayesian Estimation

Abstract

In recent years, almost every manufacturing site has been supported by a lot of part-time, temporary, or mid-career personnel, given the poor state of the economies all over the world. However, expert managers of front-line workers have to design more complex methods of production planning, when urgent orders due to uncertain elements like a disaster are taken into consideration. Therefore, this paper proposes a sustainable production planning model using an inference methodology. The method was suggested by Mahadevan et al. in the field of architecture, and some cases of its effectiveness have been shown. In this paper, we try to incorporate that method into our sustainable production planning model. First, a work element that overflows into another process is assumed to be a "Dummy Moving Element (DME)". Next, DME estimation analysis and improvement using Bayesian estimation are discussed. Finally, the effectiveness of our model is verified by a numerical experiment.

A Comprehensive Analysis to Achieve Sustainable Production Planning in Uncertain Environments

“…On the other hand, it is seen that the propagation of breaking will greatly influence it. An example of Kataoka et al [8] is shown in Figure 2. The thick frame shows some observation points and the wavy frame shows some force points added to a building.…”

“…Figure 2. Example of structural failure [8] In this paper, the concept of a sustainable production planning model is adopted to a comprehensive analysis as shown in Figure 3. Because of the prior job training, it is not easy to move work elements to another production Takayuki KATAOKA, Katumi MOEIKAWA , Katsuhiko TAKAHASHI International Journal of Japan Association for Management Systems process.…”

“…Kataoka et al [8] propose mathematical formulas regarding DMEs as follows. Equation (1) shows the objective function to minimize the total number of DMEs.…”

“…The conceptual flow of Mahadevan et al [12] is shown in Figure 1. Especially, the number of elements, cycle time and urgent works is greatly increasing as compared with the case of Kataoka et al [8].…”

“…On the other hand, Muramatsu [7] shows that the ranked positional weight technique proposed is more robust than enumeration method or branch and bound method for large scale problems in heuristics methods. Kataoka et al [8] also applies the ranked positional weight technique for small scale simulation. That is the reason why it is characterized that calculation time is not largely increasing when the number of work elements on a large scale production line is increasing.…”