This research aimed to establish the power transformer fault management system by applying Sustainable Industrial Management Engineering (SIME.) method. The research tools were electrical and chemical testing. As power transformer is usually huge when it is damaged the possible way to manage such damage is to send such power transformer to the manufacturer’s plant for repair which requires long period of time and high costs of repair. As a result the researcher therefore establish the power transformer fault management system as a tool for assessing damage to decide whether power transformer repair should be instead done at the power station or not in order to decrease the number of power transformer returned to the manufacturing plant for repair. This would eventually help reduce costs and time for repairing power transformer and allows faster period of reuse of power transformer concomitantly. According to the result it would found that the power transformer fault management system by applying Sustainable Industrial Management Engineering (SIME) method could be used as guidance for decision making to have power transformers repaired at the power station as much as possible. This could help reduce average time spent for repair by 84.44 percent with the cost reduction by 68.62 percent when comparing to returning power transformers to the manufacturing plant. This could also be applied in planning for power transformer maintenance prior to the occurrence of any damage to power transformers further.

This research proposes reliability analysis in order to find the probability that a machine will work properly the failure rates of a machine and the factors related to the failure rates. The data were collected from 8 types of machines in an autoparts manufacturing factory. They consist of the times measured from the first day of the study until the machine produces defective product workers and production steps. The study duration is 90 days. The results show that the probability that the machine type 4 will work properly more than days is 0.40 machine type 5 more than 68 days is 0.32 machine type 6 more than 72 days is 0.31 machine type 8 more than 85 days is 0.26 machine type 9 more than 109 days is 0.80 machine type 10 at more than 52 days is 0.38 machine type 11 more than 71 days is 0.32 and the probability that the machine type 12 will work properly more than 85 days is 0.26. The failure rate of the machine type 4 at day 51 is 6.61 machine type 5 at day 68 is 1.61 machine type 6 at day 72 is 0.77 machine type 8 at day 85 is 1.26 machine type 9 at day 109 is 1.31 machine type 10 at day 52 is 0.92 machine type 11 at day 71 is 1.24 and the failure rate of the machine type 12 at day 85 is 2.15. The factors influencing on the failure rates are worker group 2 and production step 3 at the significance of 0.05.

Pure water was consumed and insufficient that causes from the population continuous increasing. The water was contaminated with some pollutants. The most of science laboratory produced only the distillation water for experimental learning. In present distillation technology was released a lot of wastewater. Therefore a research group interested in applies to use value engineering for water resource management. This research collected the data analysis of distillation water process and designed of renewable wastewater for cooling process. The results shown that before improve system a distillation water and wastewater were found 3.7 l/h and 140.3 l/h respectively. For after improve system a distillation water was found only 3.82 l/h and without wastewater. Furthermore economical study found that the cost of water and electric were saved 394.23 bath/month when compared with old system. And the payback period was 114.16 month (9 years 6 months 3 days). Hence the applied value engineering for water resource management could be saved wastewater 100 percent.

Kansei engineering or effective engineering is an important product development methodology in which users’ or customers’ feelings and demands on the product are translated into important parameters for product design. On the other hand effective engineering is an application of users’ opinion mood and feelings in product design which seems to guarantee that the product will meet the demand of customers. This idea was first developed in early 1970s in Japan. Now it is widely used in both Asian countries such as Japan Korea Taiwan and European countries such as Sweden Spain and France. It is widely used in various fields like applied science and psychological science. This paper discusses the application of Kansei engineering in various daily-used products in both Japanese and Western lifestyles. The perspectives presented in this article are based on the authors’ engineering knowledge.

In software engineering requirements from customers users and stakeholder are initial information for software development process. The requirements elicited and gained are defined classified refined and stored systematically according to needs management principles. Therefore the requirements would be correct and ready to be used in the next step of development process. This process is called Software Requirements Engineering. If the gained software requirements are incorrect lack quality or are managed unsystematically they could lead to project failure and low-quality software product which cannot meet the needs of users and stakeholders. For these reasons this article proposed an overview of software requirements and an approach for software requirements management level of software requirements quality of software requirements and understanding of quality aspect common problems of requirements elicitation and awareness of impact and damage due to incorrect or low quality requirements. Success factors of software requirements management and 1-10-100 rules are also discussed. Finally the article addresses roles and goals of software requirements management team.