Application al. [3]. The process capability analysis can be

Application of Process Capability Indices to
Measure Performance of Manufacturing Process


Kwek Yan Ping

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Applied Science and Technology, University Tun Hussien Onn Malaysia, Malaysia


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The process capability indices (PCIs) are used to evaluate and monitor
the process of manufacturing industry. The PCIs that used in the manufacturing industry are




. The machine capability is calculated by


 which is in short period. The PCIs are
important in manufacturing industry.

Keywords. Process
capability indices; Machine capability.


A process in the manufacturing industry is very unique because the process needs the linkages of manpower, raw materials, machines, and
methods. The linkages are the variation
of the process that are hard to control. In order to improve the quality level
of products, the capability of the process plays an important role in the manufacturing industry. Rezaie, K. 6. The process capability indices
(PCIs) is also known as process capability
analysis which is widely used in manufacturing industry. The PCIs is
used to measure the ability of the process to meet the requirements of the
customers which are also known as specification limits. The analyst used PCIs
to control and monitor the performance of the process in the manufacturing industry. Besides, the PCIs can use to improve the performance of the process by reducing the variation of the
process. JH, S. et al. 3.

The process capability analysis can be presented graphically by using
histogram and probability plot. The histogram and probability can show the
result of PCIs visually.
Montgomery, D. C. 5. The graphics can determine whether the process is
within specification limits (SLs) or not. Steiner, S. et al. 9. The
histogram is the easiest and clear method to determine the performance of the process. If the process is in
control and the data is normally distributed, the potential capability analysis
can be used to improve the quality of the process. Spano, A. 8. By referring to the
histogram, we can determine whether the process is off centering or not. The
PCIs is used to compare the output of in control process with the SLs by 6 sigmas. PCIs are quantitative measures based on the performance and potential of the
process. By doing so, the process can meet the requirements of the customers.
Rezaie, K. et al. 6.


The process of the manufacturing
industry is considered as capable when the process is under control. Spano, A.
6. The automotive industry was applying the PCIs in Japan and United States
(US). The process capability with sampling properties and estimation procedures
is measured to determine the normality of the process and the process is in
statistical control or not. Kane, V.E. 4. The PCIs had been used in
manufacturing industry in quantitative form to ensure the performance of the
process. The numerical data will help the person in charge can modify the
process by using more efficient methods. The cost spent in the process of
rework and scrap will cause the loss of the industry. Hence, the high-quality production should practice in
industry and try to meet the requirements. JH, S. et al. 3. The PCIs is the
best method to maintain the quality of the product.

According to the requirements of the
customers with the costs that needed to spend
by the suppliers, the suppliers still need to set the suitable cost for their
product and ensure that the products are under tolerance limits. If the process capability of the process is under
control by the suppliers, we can try to
improve the quality of products or the process by out of control action plan
(OCAP). The process capability indices
can help to analyze the capability and
try to predict the machining process that can meet the expectations and
tolerance limits of the customers. The process capability indices consist of




. Abhijit S. et al., Montgomery, D. C. 1, 5. The

will represent the performance of process. Table 1 summaries the six quality
condition with its

?hsan K.2. The different

will represent different quality condition.

Table 1: Quality conditions and


Quality condition


Super excellent

2.00 ?


1.67 ?

 ? 2.00


1.33 ?

 ? 1.67


1.00 ?

 ? 1.33


0.67 ?

 ? 1.00




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