De Martino, Massimiliano (2020) A Multi-Attribute Task Sequencing Optimization with Neighbourhoods Method to Improve Quality in Sustainable Industrial Processes. [Tesi di dottorato]

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Item Type: Tesi di dottorato
Resource language: English
Title: A Multi-Attribute Task Sequencing Optimization with Neighbourhoods Method to Improve Quality in Sustainable Industrial Processes
Creators:
CreatorsEmail
De Martino, Massimilianomassimiliano.demartino@unina.it
Date: 31 March 2020
Number of Pages: 106
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Industriale
Dottorato: Ingegneria industriale
Ciclo di dottorato: 32
Coordinatore del Corso di dottorato:
nomeemail
Grassi, Michelemichele.grassi@unina.it
Tutor:
nomeemail
Patalano, StanislaoUNSPECIFIED
Timpone, FrancescoUNSPECIFIED
Date: 31 March 2020
Number of Pages: 106
Keywords: Task sequencing, TSPN, Industrial Processes
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/15 - Disegno e metodi dell'ingegneria industriale
Date Deposited: 02 Apr 2020 11:18
Last Modified: 05 Nov 2021 13:07
URI: http://www.fedoa.unina.it/id/eprint/13250

Collection description

Industrial world faces what is commonly recognized as fourth industrial revolution, also known as ‘Industry 4.0’.Industry 4.0 requires an overall production process optimization which deals with many manufacturing industrial aspects. Consider all sources of industrial optimization is not a trivial task. This dissertation deals with some of them which have a huge impact on Industry 4.0 fundamental, which are: • Robot Path Planning Optimization • Defects Impacts Reduction • Workers’ condition improvement Compared to great efforts made in the last years, a strategy for a production with no defects has not been completely inside industries companies, so quality process must rectify defects to avoid waste of resources. Quality process is realized by human resources manually leading to waste of human resources and significant ergonomics risk factors as awkward posture in handling job task; moreover although people are very good at this task and sometimes even better than machines, they cannot work for long periods of time as their eyes get tired, muscles and tendon could be overloaded, compromising operator’s health and quality of the work. Automate the quality control process will bring undoubted advantages in various aspects, as the improvement of the ergonomics workplace, optimization of the process as regards processing times, and quality of the production output. The dissertation addresses the following questions: How to define a new kind of workstation which can be applied to a wide range of industrial application to achieve: • Improvement in ergonomic workspace aspects • Reduction in defects number and impact Optimization in robot task execution by means of a methodology minimising computational time to enable dynamic robot programming in the case of multiple and coupled tasks’ attributes Starting from this question, following contributes have been addressed: 1. How to find optimal task sequence in case of not simple shapes with partial or total overlap using Euclidean distance as key metric a. Define an operator able to define when to pass through overlap zones 2. How to define an attribute to evaluate and forecast collision between robot and human, considering all robot parts, starting from multi-attribute approach to find optimized task sequencing 3. How to use computer-based method to develop a tool for image recognition on a reflecting surface.

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