This Company is one of the largest multipurpose port in Malaysia which provides facilities
and services to handle variety of cargoes ranging from containers, cars, break bulk cargoes, dry bulk
cargoes and liquid bulk cargoes. The company divided into three main core business divisions which
are Container Division, Conventional and Logistics Services and Marine Divisions. Based on Pareto
analysis, Conventional & Logistics Services has the highest number of accidents with 75% of total
number of accidents in year 2014. In this company, the trend analysis of accident keep increasing
month by month. In this study using DMAIC approach, the objectives of this study is to improve safety
performance by decreasing the number of accident focused on Conventional & Logistics Division by
using six sigma approach. Six sigma is a quality tools for process improvement. It involved five phases
which using many quality tools to identify problem and improves the process. The data being analysed
by using statistical method and graph. As conclusion, the average number of accident decrease from
7.33 to 7.25 and the trend analysis shows decline graph compared to before. Based on the hypothesis
testing, using the p-value, it was found the shift pattern, safety culture (unsafe act unsafe condition
report submission), accidents location, type of activity and contractors have significance impact to
number of accident. Meanwhile, number of tonnage handled (productivity) and number of man-hour
does not have significance impact to the number of accident. It was also found that there is no
significance between numbers of accident happen at night shift, morning shift or afternoon shift. It can
be concluded that, the six sigma approach are suitable method to analyse accident and can be a
significance approach in determining the root cause of accident in the company.
Optimum design of HEN can cause significant reduction in the total cost of the plant.
Targeting method using pinch analysis diagrams was presented to find out investment cost required
and the period of return of the investment of optimization of the refinery system. This method can be
done by knowing the amount of ΔTmin and by pointing the composite curve of saving vs investment (S-I
curve).The targeting method is the modification of the system that need to be done to avoid movement
of heat exchangers in order to minimize the return of the investment. This method can assist refineries
management to make decision in order to optimize the refinery system.Result shows that refinery can
reduce the temperature on the main tower until 9.65MW and the investment will be $360,000 with the
time of the return cost being 7.7 months