Statistical Process Control of assembly lines in a manufacturing plant: Process Capability assessment

PT Sankei Dharma Indonesia merupakan perusahaan yang bergerak di bidang otomotif. Salah satu produk yang dihasilkan adalah nut (berfungsi sebagai dudukan kabel sensor). Proses nut dianggap critical to quality, dimana hasil dari proses memperhatikan inside diameter nut yang dihasilkan PT A, PT B, dan PT C. Peningkatan kinerja proses dilakukan dengan menggunakan process capability yang merupakan salah metode dari Statistical Process Control. Hasil dari penelitian menunjukkan bahwa process capability pada inside diameter PT B berjalan dengan tidak sesuai, di mana nilai capability index Cp = 0.57, Cpl = 0.58, Cpu = 0.56, Cpk = 0.56, dan Cpm = 0.54. Sedangkan process capability pada inside diameter PT A dan PT C tergolong sangat memuaskan. Di mana nilai capability index PT C Cp = 2.34, Cpl = 2.37, Cpu = 2.30, Cpk = 2.30, dan Cpm = 2.26. Dan nilai capability index PT A Cp = 1.77, Cpl = 1.79, Cpu = 1.75, Cpk = 1.75, dan Cpm = 1.86. AbstractPT Sankei Dharma Indonesia is a company engaged in the automotive field. One of the resulting product is a nut (functioning as a sensor cable holder). Nut process is considered critical to quality, which result from the attention generated inside diameter nut PT A, PT B, dan PT C. Improved performance of process is done by using process capability, which is one method of Statistical Process Control. Results from the study showed that the process capability to the inside diameter of the PT B running is not appropriate, in which the value of capability index Cp = 0,57; Cpl = 0,58; Cpu = 0,56; Cpk = 0,56, dan Cpm = 0,54; While the process capability to inside diameter PT A and PT C as very satisfactory. Where the value of capability index PT C Cp = 2.34, Cpl = 2.37, Cpu = 2.30, Cpk = 2.30, dan Cpm = 2.26. And the value of capability index PT A Cp = 1.77, Cpl = 1.79, Cpu = 1.75, Cpk = 1.75, dan Cpm = 1.86.

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The Application Research of Statistical Process Control in Quality Management

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.926-930.4000 ◽

2014 ◽

Vol 926-930 ◽

pp. 4000-4003

Author(s):

Qiu Yan Liu ◽

Jun Li Shi ◽

Shi Yuan Xing

Keyword(s):

Quality Management ◽

Process Control ◽

Statistical Process Control ◽

Control Chart ◽

Process Capability ◽

Control Technology ◽

Application Research ◽

Statistical Process ◽

Intensity Index ◽

Productive Process

By discussing the application of statistical process control technology in the print and package industry, we have been in control of the productive process, for focusing on the heat-seal intensity index of sauce package products, and utilized instability of the control chart discovering the instable in the process , to realize the pre-alarm function. The management makes the process update constantly, and enhances the process capability.

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Implementation of Statistical Process Control through PDCA Cycle to Improve Potential Capability Index of Drop Impact Resistance: A Case Study at Aluminum Beverage and Beer Cans Manufacturing Industry in Indonesia

Quality Innovation Prosperity ◽

10.12776/qip.v24i1.1401 ◽

2020 ◽

Vol 24 (1) ◽

pp. 104 ◽

Cited By ~ 1

Author(s):

Sunadi Sunadi ◽

Humiras Hardi Purba ◽

Sawarni Hasibuan

Keyword(s):

Process Control ◽

Statistical Process Control ◽

Manufacturing Industry ◽

Impact Resistance ◽

Process Capability ◽

Drop Impact ◽

Nominal Group ◽

Statistical Process ◽

Capability Index ◽

Pdca Cycle

Purpose: The purposes of this study are first, to analyze why the process capability index (Cpk) for drop impact resistance (DIR) does not meet the specification or less than 1.33, and second, to find out what improvements should be made to make it meet the specification.Methodology/Approach: The methodology used was Statistical Process Control (SPC) through the PDCA cycle, supporting with Cause and Effect Diagram (CED), Nominal Group Technique (NGT) and “why, what, where, when and how (5W1H)” method.Findings: With the above methods, the result of the study was given a positive impact on the company. The average of DIR was increased from 20.40 cm to 25.76 cm, increased by 26.27% and the standard deviation was reduced from 1.80 to 1.48, and then the Cpk index was increased from 0.48 to 1.79 it means the process is in control and capable.Research Limitation/implication: This research was limited only on the two-piece can aluminum cans manufacturing process, no for three-piece cans manufacturing. SPC through PDCA cycle is an interesting method for continuous improvement of process capability in the cans manufacturing industry.Originality/Value of paper: This study highlights the area of future research SPC through the PDCA cycle to analyze and optimize process capability. Therefore, this research is considered to promote and adopt high-valued methodologies for supporting industry to achieve global competitive advantages.

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Retrospective analysis for phase I statistical process control and process capability study using revised sample entropy

Neural Computing and Applications ◽

10.1007/s00521-018-3556-4 ◽

2018 ◽

Vol 31 (11) ◽

pp. 7415-7428 ◽

Cited By ~ 1

Author(s):

Shing I. Chang ◽

Zheng Zhang ◽

Siim Koppel ◽

Behnam Malmir ◽

Xianguang Kong ◽

...

Keyword(s):

Process Control ◽

Phase I ◽

Retrospective Analysis ◽

Statistical Process Control ◽

Process Capability ◽

Sample Entropy ◽

Statistical Process

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Application of Statistical Process Control Tools to Improve Product Quality in Manufacturing Processes

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.110-116.4023 ◽

2011 ◽

Vol 110-116 ◽

pp. 4023-4027

Author(s):

Omar Bataineh ◽

Abdullah Al-Dwairi

Keyword(s):

Quality Control ◽

Process Control ◽

Statistical Process Control ◽

Control Charts ◽

Process Capability ◽

Manufacturing Processes ◽

Statistical Process ◽

Free Products ◽

Drug Companies

Quality control and improvement at the process level is a vital activity for the achievement of defect-free products in various manufacturing processes. This study employs statistical process control (SPC) tools such as control charts and process capability ratio for quality control and improvement. The control charts employed are , R and the cumulative-sum (CUSUM). The process capability ratio used is the so called process capability index (PCI). These tools have been implemented with the aid of Minitab® statistical software. In this study, the manufacturing process of gelatin capsules is investigated in terms of quality of the capsules, which are produced and shipped for use by various drug companies. As a result of implementation of SPC tools, an expected reduction in the number of defective capsules by 29% relative to the stage before implementation was achieved.

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Statistical process control application on service quality using SERVQUAL and QFD with a case study in trains’ services

The TQM Journal ◽

10.1108/tqm-02-2014-0026 ◽

2016 ◽

Vol 28 (2) ◽

pp. 195-215 ◽

Cited By ~ 17

Author(s):

Hadi Akbarzade Khorshidi ◽

Sanaz Nikfalazar ◽

Indra Gunawan

Keyword(s):

Process Control ◽

Service Quality ◽

Statistical Process Control ◽

Control Charts ◽

Quality Function Deployment ◽

Process Capability ◽

Statistical Process ◽

Content Type

Purpose – The purpose of this paper is to implement statistical process control (SPC) in service quality using three-level SERVQUAL, quality function deployment (QFD) and internal measure. Design/methodology/approach – The SERVQUAL questionnaire is developed according to internal services of train. Also, it is verified by reliability scale and factor analysis. QFD method is employed for translating SERVQUAL dimensions’ importance weights which are derived from Analytic Hierarchy Process into internal measures. Furthermore, the limits of the Zone of Tolerance are used to determine service quality specification limits based on normal distribution characteristics. Control charts and process capability indices are used to control service processes. Findings – SPC is used for service quality through a structured framework. Also, an adapted SERVQUAL questionnaire is created for measuring quality of train’s internal services. In the case study, it is shown that reliability is the most important dimension in internal services of train for the passengers. Also, the service process is not capable to perform in acceptable level. Research limitations/implications – The proposed algorithm is practically applied to control the quality of a train’s services. Internal measure is improved for continuous data collection and process monitoring. Also, it provides an opportunity to apply SPC on intangible attributes of the services. In the other word, SPC is used to control the qualitative specifications of the service processes which have been measured by SERVQUAL. Originality/value – Since SPC is usually used for manufacturing processes, this paper develops a model to use SPC in services in presence of qualitative criteria. To reach this goal, this model combines SERVQUAL, QFD, normal probability distribution, control charts, and process capability. In addition, it is a novel research on internal services of train with regard to service quality evaluation and process control.

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