Acceptance control chart considering practical significance using process capability indices: proposal of a predictive method and development of software

• Grant number: 17/08861-6
• Support Opportunities: Regular Research Grants
• Start date: December 01, 2017
• End date: November 30, 2019
• Field of knowledge: Engineering - Production Engineering
• Principal Investigator: Pedro Carlos Oprime
• Grantee: Pedro Carlos Oprime
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated researchers: Fabiane Letícia Lizarelli ; Márcio Lopes Pimenta

Abstract

Two methodological alternatives emerge in decision-making processes that are little explored: the use of statistical methods with levels of statistical significance, or, what is common, the use of judgment based on practical and economic significance. In this line, the proposed research theme refers to control chart studies that simultaneously adopt the two decision approaches: statistical significance and practical significance. The choice of the research theme stems from the search for answers to the questions: i) Why do control charts fail, given that this subject has been researched for more than six decades? (Ii) Why do not these researches incorporate into their methods significance levels based on practical and economic aspects, such as the operational constraints of action on processes and the effects of non-compliance with customer specifications? To answer these questions, this project will be based on theories of acceptance control charts and process capability indices, two fundamental aspects from a practical point of view. With the integration of these elements - practical significance, acceptance control charts and process capability indices - we intend to develop new types of control charts aligned with the demands of manufacturing companies. The proposed method for this purpose is the statistical modeling to obtain numerical solutions by means of mathematical and simulation methods, with field research in companies that adopt statistical process control. With the search of field information, it is intended to build new bases for the use of statistical control charts. The expected product is the development of software to support the construction of graphs of statistical control of Cp and Cpk, which is also useful in studies of machine capacity applied in the purchase of machines and in the validation of processes. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

OPRIME, PEDRO CARLOS; LIZARELLI, FABIANE LETICIA; PIMENTA, MARCIO LOPES; ACHCAR, JORGE ALBERTO. RELIABILITY PAPER Acceptance X-bar chart considering the sample distribution of capability indices, Cp and Cpk A practical and economical approach. INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, v. 36, n. 6, p. 875-894, 2019. (17/08861-6)

FARIA SOBUE, CASSIO EDUARDO; JARDIM, FELIPE SCHOEMER; CAMARGO, VICTOR CLAUDIO BENTO; LIZARELLI, FABIANE LETICIA; OPRIME, PEDRO CARLOS. Unconditional performance of the X over bar chart: Comparison among five standard deviation estimators. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, v. 36, n. 5, MAY 2020. (17/08861-6)

SORDAN, JULIANO ENDRIGO; OPRIME, PEDRO CARLOS; PIMENTA, MARCIO LOPES; CHIABERT, PAOLO; LOMBARDI, FRANCO. Lean Six Sigma in manufacturing process: a bibliometric study and research agenda. TQM JOURNAL, v. 32, n. 3, p. 19-pg., 2020-05-05. (17/08861-6)

OPRIME, PEDRO CARLOS; PIMENTA, MARCIO LOPES; JUGEND, DANIEL; ANDERSSON, ROY. Financial impacts of innovation in Six Sigma projects. TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE, v. 32, n. 7-8, JULY 2019. (17/08861-6)