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Analysis of manufacturing processes according to FMEA techniques and Implementation of IoT systems to prevent process failures.

Sendura Vel Anandavel

Analysis of manufacturing processes according to FMEA techniques and Implementation of IoT systems to prevent process failures.

Rel. Paolo Chiabert. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2021

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Abstract:

Analysis of manufacturing processes according to FMEA techniques and Implementation of IoT systems to prevent process failures. Operating processes within service or manufacturing organizations are never perfect. On any given day, challenges can surface that cause the organization to deviate from its target objectives. Manufacturing and Process Engineers envision a process is free of errors. Unfortunately, errors and especially errors propagated when people are present can be quite catastrophic. Knowing that uncertainty exists, the key to successful Operations Management lies in appropriate preparedness which involves building contingencies in place, that facilitate your organization’s restoration. In its usual systematic fashion, Six Sigma Methodology offers a tool called Process Failure Mode Effects Analysis (PFMEA) to achieve this objective. Process Failure Mode and Effects Analysis (PFMEA) looks at each process step to identify risks and possible errors from many different sources. Here a simple manufacturing process in which the tablets are manufactured by Belloni Eccentric punch machine. For this manufacturing processes, PFMEA is applied to calculate the possible risks and errors from various factors. And some IoT systems were used to control the process failures. To throw a better insight and understanding, this project gives an overall idea of PFMEA application on a simple manufacturing process and wide knowledge about IoT systems that helps to improve any given system in a efficient and effective way . The Project also explains how to implement and execute these tools to product or process for smart manufacturing Pharma facility.

Relators: Paolo Chiabert
Academic year: 2021/22
Publication type: Electronic
Number of Pages: 74
Subjects:
Corso di laurea: Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo)
Classe di laurea: New organization > Master science > LM-33 - MECHANICAL ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/20764
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