Implementation of FCAUP – a framework for conformity assessment inspired by the uncertainty principle

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Data

2021-10-28

Autores

Moraes, Celso Francisco de [UNESP]
Silva, Messias Borges [UNESP]
Sawhney, Rapinder

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Purpose: The purpose of this paper is to report the first practical applications of FCAUP (Framework for Conformity Assessment inspired by the Uncertainty Principle) carried out using a pilot implementation in a boat trailer manufacturer company in Maryville, Tennessee, USA and a practical application in a metrology company in São José dos Campos, São Paulo, Brazil. Design/methodology/approach: Field studies have been conducted in two different companies: a pilot implementation during the preparation activities of the acceptance inspection of finished products and a practical application during the internal audit related to the quality management system. Findings: (1) partial double inspection is advantageous in conformity assessment; (2) a structured procedure tends to reduce the risks arising from the use of partial double inspection; (3) the recommended amount of double inspections is directly proportional to the uncertainty involved in the process and it is inversely proportional to the degree of trust in a presumed conformity status. Research limitations/implications: This novel framework is for practitioners in manufacturing industries and test laboratories. Practical implications: The results of these practical applications suggest that FCAUP is a consistent approach to be used in several categories of conformity assessment in manufacturing industries and test laboratories due to the balance between result and time (cost). Originality/value: This new framework, named FCAUP, for planning and executing conformity assessment activities has been introduced in a theoretical study published by Moraes and Silva (2018) and it is based on an analogy with the Uncertainty Principle of Quantum Mechanics.

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Acceptance inspection, Audit of quality management system, Conformity assessment, FCAUP, Uncertainty principle analogy

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TQM Journal, v. 33, n. 6, p. 1069-1099, 2021.