scholarly journals Implementation of statistical process control for quality control cycle in the various industry in Indonesia: A systematic literature review

2021 ◽  
Vol 13 (2) ◽  
pp. 194
Author(s):  
Hibarkah Kurnia ◽  
Setiawan Setiawan ◽  
Mohammad Hamsal
Keyword(s):  
Systematic Review ◽  
Quality Control ◽  
Literature Review ◽  
Process Control ◽  
Statistical Process Control ◽  
Systematic Literature Review ◽  
Statistical Process ◽  
Software Production ◽  
Research Questions ◽  
Production Software

A systematic literature review is a rigorous method of assessing and combining research results compared to the usual literature review, which consists of annotated bibliographies, a systematic review of the existing literature regarding specific research questions on a topic of interest. Statistical Process Control (SPC) is a well-established technique in a context that has recently been used in software production. Software production is not like manufacturing because it requires more human resources and machines, resulting in an item's one-time production. It is therefore essential to assess what SPC works in a software context. Thus, this consideration has motivated us to define and conduct an evaluation review to assess whether SPC is used effectively and genuinely Quality Control Cycle (QCC) in Indonesia's various industries. According to a systematic literature review process, an established protocol was revised and refined by the authors. This journal collection of journals has been used in various industries in Indonesia. We report our preliminary considerations and results in a systematic review on the SPC and find 30 journals collected as references for readers in making research journals related to SPC. Our products and first impressions are favorable. This journal collection can also make it easier for researchers to get the desired journal references. 

scholarly journals ANALISIS KUALITAS PRODUK MENGGUNAKAN METODE STATISTIC PROCESS CONTROL (SPC) MINITAB DAN TIME-CHARTING DI PT. COCA-COLA BOTTLING INDONESIA UNIT LAMPUNG

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Joko Saryono ◽  
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Method ◽  
Production Data ◽  
Statistical Process ◽  
Research Results ◽  
Statistic Process Control ◽  
Gas Volume ◽  
A Company

Abstract PT. COCA-COLA BOTTLING INDONESIA is a company engaged in the field of Agro-industry is bottling soft drinks and not sparkling. The products produced are Coca-Cola, Sprite, Fanta, and Tea. To be able to compete with similar industries then the company implements quality control by Statistical Process Control method. In the development of this SPC many methods there are manual or who use the software. Currently PT. Coca-Cola Bottling Indonesia in quality control using Time Charting method, but since the transition from Minitab to Time Charting the tendency of the value of capability below standard, whereas production data is almost the same as using Minitab. The purpose of this research is to analyze the inequality of Statistical Process Control between Minitab 13 and Time Charting. Time Charting method is a new method that is given by the headquarters for the process of quality control can be fast and accurate. Quality control with the Statistical Process Control of Minitab and Time Charting methods after the results of the research results was found to be part of different LSL and USL charging, and Calculate Statistic Using different from Minitab method should still be 6 but in written procedure 3. For writing LSL And USL if the Time Charting is determined by the head office while Minitab analysts fill in based on experiments on the decrease of gas volume marketed in previous years. From the research results obtained Cpk data for Minitab method 13 is Sprite 390 ml 1.47, Sprite 1000 ml 1.90 and Sprite 1500 ml 1.38. The result of the research was using Minitab method and the Charting Time of Capacity that is above 1.33 average. The causes of the resulting inequality of both methods are the LSL, USL and Calculate Statistic Using values. The smaller the value of Calculate Statistic Using the higher Cpk produced. Keywords: Production, Statistical Process Control, Quality.

The Intelligent Quality Control Technology System Based on the Integration Methods of SPC and EPC

2012 ◽  
Vol 263-266 ◽  
pp. 839-842 ◽  
Author(s):  
Zhong Qiu Jiang
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Process ◽  
Control Mode ◽  
Statistical Process ◽  
Technology System ◽  
Quality Control Process ◽  
Dynamic Quality ◽  
And Function

SPC (statistical process control) and EPC (engineering process control) is the scientific methods of quality quality control and quality improvement. It is the difficult problems of quality control process for network manufacturing enterprise how to effectively solve the dynamic quality fluctuation monitoring and the fluctuation abnormal diagnostic analysis and timely process adjustments, this paper designs the intelligent quality control mode and function system architecture, the modes expatiates quality management network based on quality control network of the workshop level and enterprise class network, and researches the integration applications of statistical process control and enterprise ERP quality system, and applies J2EE technology to achieve the system organic combination of design and development.

Quality Control of Plastic Cup Products Using Statistical Process Control Methods and Failure Modes and Effect Analysis

2019 ◽  
Vol 7 ◽  
Author(s):  
Kurniawan Eka Rusandi ◽  
Wiwik Sulistiyowati
Keyword(s):  
Quality Control ◽  
Process Control ◽  
Statistical Process Control ◽  
Failure Modes ◽  
Total Production ◽  
Statistical Process ◽  
Effect Analysis ◽  
A Value ◽  
Fmea Analysis ◽  
Cup Products

PT. ICP is a company engaged in manufacturing of packaging, with a wide variety of packaging technologies that fit the needs of the current market share. Among the resulting product is aplastic cup, the results of thermoforming. This research aims to know the main cause of the defect (defect) in a plastic cup products and to reduce product defects in the production process. From the results of the observations made in September 2017 until December 2017 known that the plastic cup products with total production of 63,314,964 pcs to 3,671,341 pcs disability amount. Based on the problems faced by the company efforts on product quality control plastic cup to find the cause of a disability and find solutions for improvement. Proper methods used in the problems that occurred in PT ICP are using Statistical Process Control (SPC) and the method of Failure Mode and Effects Analysis (FMEA). The method is intended to reduce defects in the product and look for the main cause of defect products in a plastic cup. From the results of research conducted has been known that the biggest cause of disability plastic cup is of a rough lip with disabilities amount of 1,346,308 pcs with a cumulative value of 42%. FMEA analysis and the results of that unknown cause rough lip is from wear cutting factor with a value of 224 RPN.

scholarly journals A Quality Control Scheme for a Commercial Pozzolana Plant: A Case Study of Pozzolana Ghana Ltd

2019 ◽  
Vol 60 (2) ◽  
pp. 74-83
Author(s):  
J. Sarfo-Ansah ◽  
K. A. Boakye ◽  
E. Atiemo ◽  
R. Appiah
Keyword(s):  
Mechanical Properties ◽  
Quality Control ◽  
Compressive Strength ◽  
Process Control ◽  
Statistical Process Control ◽  
Setting Time ◽  
Mechanical Tests ◽  
Statistical Process ◽  
Control Scheme ◽  
Quality Control Scheme

A Quality control scheme was developed for a 200 ton per day commercial pozzolana plant. The scheme was evaluated for the first 34 days of production. Statistical Process Control tech­niques were specifically applied to the mechanical properties of setting times and compressive strength. Results obtained showed that pozzolana samples tested were chemically suitable with total SiO2, Al2O3 and Fe2O3 content ≥ 70%. Mechanical tests performed were mostly under control and when out-of-control, they gave valuable indication to plant malfunction or operator errors which were promptly corrected. The results of mechanical properties tested against the three major brands of cement on the Ghanaian market showed that pozzolana gave highest compressive strengths with Dangote CEM I 42.5R ranging between 21.3 MPa - 36.3 MPa at 7 days and 33.8 MPa - 45.1 MPa at 28 days whilst lowest compressive strengths were obtained with Ghacem CEM II B-L 32.5R cement ranging between 16.3 MPa – 23.6 MPa at 7 days and 23.3 MPa – 30.7 MPa at 28 days. Compressive strengths obtained with Diamond CEM II B-L 42.5N cement were average. A mean compressive strength for all brands of ce­ment of 25.2 MPa and 33.6 MPa at 7 days and 28 days respectively were obtained. Keywords: Pozzolana cement, statistical process control, Shewhart chart, compressive strength, setting time

scholarly journals Microservice security: a systematic literature review

2022 ◽  
Vol 7 ◽  
pp. e779
Author(s):  
Davide Berardi ◽  
Saverio Giallorenzo ◽  
Jacopo Mauro ◽  
Andrea Melis ◽  
Fabrizio Montesi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Distributed Systems ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Widespread Adoption ◽  
Research Questions

Microservices is an emerging paradigm for developing distributed systems. With their widespread adoption, more and more work investigated the relation between microservices and security. Alas, the literature on this subject does not form a well-defined corpus: it is spread over many venues and composed of contributions mainly addressing specific scenarios or needs. In this work, we conduct a systematic review of the field, gathering 290 relevant publications—at the time of writing, the largest curated dataset on the topic. We analyse our dataset along two lines: (a) quantitatively, through publication metadata, which allows us to chart publication outlets, communities, approaches, and tackled issues; (b) qualitatively, through 20 research questions used to provide an aggregated overview of the literature and to spot gaps left open. We summarise our analyses in the conclusion in the form of a call for action to address the main open challenges.

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