Conference article

New Method of Control Charts Analysis

Adam Hamrol
Poznan University of Technology, Poland

Agnieszka Kujawinska
Poznan University of Technology, Poland

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Published in: 10th QMOD Conference. Quality Management and Organiqatinal Development. Our Dreams of Excellence; 18-20 June; 2007 in Helsingborg; Sweden

Linköping Electronic Conference Proceedings 26:121, p.

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Published: 2008-02-15


ISSN: 1650-3686 (print), 1650-3740 (online)


Quality can mean different things to different people. Quality may be thought to have two main divisions: the quality of a manufactured product and the quality of services received. From the manufacturing standpoint the quality is simply conformance to specifications.

Total quality in an organization means simply the quality work that is expected in every job. There are no exemptions. When something is done; it should be done right in the first time. When a product is made; it should be defect-free. When a service is provided; the customer should be pleased with the result.

There is a variety of definitions of quality attributed to the historical leaders in the quality evaluation. Walter Shewhart; the author of quality control via control charts; described quality as having both an objective and a subjective side. The objective part of quality relates to measurement specifications with minimum of variation from target values. The subjective side relates to the commercial value (costs; use and esthetics). Joseph Juran described quality as “fitness to use”. Edwards Deming claimed that quality was in the eye of the beholder. For the consumer; quality represented satisfaction at a price that the consumer was willing to pay. Phil Crosby defined quality as “conformance to requirements” (Juran; 2000).

The various definitions aren’t contradictory in any way. They depend more on the focus of the definer. In a few words; quality is: fitness to use; conformance to specifications; producing the very best product; excellence in products and services; total customer satisfaction and exceeding customer’s expectations.

When a company produces a product or services; it utilizes many interrelated processes and each process includes several or many steps to accomplish a specific task. There may be several sources of data. All different processes are combined to yield the final product or service.

Statistical Process Control (SPC) is a procedure in which data is collected; organized; analyzed and interpreted so that a process can be maintained at its present level of quality or improved to a higher level of quality. SPC can be applied wherever work is being done. Initially; it was applied to production processes; but it has evolved to any work where data can be gathered. SPC involves the use of statistical signals to identify sources of variation; to improve performance and to maintain control of processes at higher quality level. SPC leads to a system of prevention which will replace the system of detection. Statistical signals are used to improve a process systematically so that production is maintained (Dietrich; 2000).

Statistical process control can improve quality by reducing product variability and can lead to improvements in production efficiency by decreasing scrap and rework. SPC is a trouble indicator. For each statistical application; such as control charts; histograms; there is an excepted form or pattern. When the actual form or pattern differs from the excepted; it is usually a signal that the problem exists. The potential problem must be investigated and eliminated. So the primary goals of SPC are: to minimize production costs – it can eliminate costs associated with making; finding and repairing or scrapping substandard products; it reduces product variability to the level that is well within specification; it leads to process predictability (Hamrol; 2005).

The basic tools for SPC are: flowchart; paretodiagram; checksheets; cause-andeffect- diagram; histogram and most important - control charts.


SPC; control charts; recognition


1. Cheng Ch. Hubele N. (1996); A pattern recognition algorithm for an x control chart. IIE Transaction 1996; nr 28

2. Dietrich E.; Szchulze A. (2000); Metody statystyczne w kwalifikacji srodków pomiarowych maszyn i procesów produkcyjnych; Wydawnictwo Notika System; Warszawa

3. Hamrol A.; Mantura W. (2001); Zarzadzanie jakoscia. Teoria i praktyka; Wydawnictwo Naukowe PWN

4. Hamrol A. (2005); Zarzadzanie jakoscia z przykladami; Wydawnictwo Naukowe PWN

5. Juran J.M.; Godfrey A.B. (2000); Juran’s Quality Handbook; McGraw-Hill

6. Woodall W. H. (October 2000); Controversies and Contradictions in Statistical Process Control; Journal of Quality Technology Session

Citations in Crossref