الگوریتم دو مرحله ای برای تغییر بخشی محصول با استفاده از AHP و PSO

This study presents a two-phase algorithm approach to deal with the issue of product part change, and the issue of supplier selection derived from the former. In the first step, Analytical Hierarchy Process (AHP) was used on expert interview records to select the module in a product that needs to be changed with top priority. In the second step, after changing the module, the supplier selection process, including building a mathematical programming model, was initiated to select the best suppliers using Particle Swarm Optimization (PSO) algorithm. We tried to use this method to maximize the value of product updating so as to extend the product life cycle, under the conditions of limited resource, and keeping the scope of change to a minimum. Finally, we selected a switchboard manufacturer as a case study to test the proposed algorithm.

At a time when the average product life cycle of a product is getting increasingly short, the significance of product part change is being recognized in stages. To maintain continuous improvement over the product line, including modifications of product weaknesses, introduction of new technologies, improvements over manufacturing processes, this optimization approach not only extends the product life cycles, but also can satisfy the needs of customers and market demand. In other words, in order to remain its product competitiveness, enterprises need a systematic approach to understand and manage the issue of product part change. Following the product part change, the supplier selection issue is another hot topic. In post-change stage, the selection of appropriate suppliers allows products of an enterprise to maintain and enhance its competitiveness in the market. Previous studies treated related issues in a different way. Once a product was considered for internal part change, it had to go through the supplier selection process for all parts, whether the parts were changed or not. However, in actual practice, when a change of product components is considered, it is not necessary to change or redesign all components because that would set off the problem of re-selection of all suppliers. Taking a notebook computer product as an example, when a model change is needed, it may be because of improved technologies relating to core components (CPU, hard disk, memory body, etc.), leading to change of certain parts necessary in the product, while the rest of the internal parts still follow the original specifications and are obtained from the original suppliers. Therefore, this study determines to look into the supplier selection issue derived from the product part change. Researchers believe that when dealing with the issue of product part change, two questions must be considered. One of them is to identify which components need to be changed with top priority, and the other one is to find appropriate suppliers following the product part change. In other words, when faced with a need to change the product, but only limited resources available, the only way out is to change product parts. Our tasks are to find out which one part (or which group of parts) needs to be changed with top priority, or, from an alternative viewpoint, which one part (or which group of parts) will create the most additional value after the product part change. Furthermore, we need to find the most suitable suppliers for such product part change. By settling these issues over the product part change, it could help an enterprise save on unnecessary costs and increase the success rate of new product marketing. To solve these two problems effectively, in this study, we have introduced a two-phase algorithm model to deal with the issue of product part change, and the issue of supplier selection derived from the former. Our problem-solving approach is based on AHP and PSO. Firstly, AHP analysis over expert interview records is conducted to find out which module in a selected product has to be changed with top priority. Secondly, the results of our analysis are optimized with PSO to find the most suitable supplier in line with such change. To verify the problem-solving method proposed in this study, a switchboard manufacturer is chosen for our experiment. The company’s existing product line is analyzed to pick out product parts that need to be changed. By the introduction of the two-phase algorithm model, we hope to create additional values for their product after such change of product parts. Then, we try to find the best supplier following the change of product parts, in order to make the whole assessment model more systematic. This study is organized in the following manner: the literature review is presented in Section 2 for understanding the issues related to product part change. Our two-phase algorithm model is introduced in Section 3. An actual case of manufactured product and related experimental results are provided in Section 4. Finally, some of the conclusions of the study are described in Section 5.

This study aims to solve the problem over the handling of product part change, and the supplier selection problem derived from the product part change. In contrast to the previous studies, this study proposes a two-phase algorithm model to deal with the problems. The first phase is to use AHP for analyzing which component of a product needs to be changed with top priority, in which each module is viewed as a separate policy to avoid the difficulty of excessive data. This algorithm approach allows us to focus on the part of a product that needs to be improved with top priority. It could avoid huge costs from re-evaluation of all component suppliers. Under the circumstances of limited resources, this algorithm allows us to make more efficient use of resources. The second phase is to settle the supplier selection issue following the product part change, including building of mathematical model to analyze various costs, and developing of PSO algorithm-based method, through which we hope to provide a set of decision-making model, including suggestions for product part change and supplier package, following the occurrence of product part change. In this study, a switchboard manufacturer is chosen for our experiment. Through the use of two-phase algorithm model, reasonable results and the best supplier package available can indeed be generated for fast decision making.