In this 21st century, manufacturing firms are facing an increasing number of challenges in the global market competition. The selection of appropriate decisions is an important aspect in the manufacturing sector. It is a well-known that the quality of available information for the decision makers is crucial in making decisions. Thus, this thesis work is aimed at reviewing available literature in the field of decision making in manufacturing, identifying the state of art research and research gaps, with the identification of a general model of decision making process from the perspective of Industry 4.0. A systematic literature review has been made by using selected keywords to search in the SCOPUS database in order to analyze the available literature related to decision making in manufacturing from 2012 to 2018. A comparative analysis was made among the different configurations of decision making process to know the pros and cons from the perspective of Industry 4.0. Results: The found papers, published in journals and many other sources, have been analyzed descriptively and briefly discussed with focus on different configurations of decision-making process. In particular it is discussed the implementation of a two stage decision model (top level and base level) on the three different configurations of decision making, in terms of : a) number of decision makers involved; b) objective of the decision makers; c) information sharing between the actors (i.e. top level and base level); d) coordination between decision makers. Research and practical implications: The quality of information and coordination of decisions are important for making decisions and with the right capacity to analyze can improve the performance of the manufacturing systems. As technologies are growing rapidly and that affects the way the decisions are made. So, Industry 4.0 is an aggregate of technology that will redefine how management and decision making are done in various organizations. Limitations: The literature review was conducted by collecting the data from the documents which were available from 2012 to 2018, by including only English language and searching only in the fields of Engineering and Decision Sciences. Another limitation was the use of only SCOPUS search database. One limitation of the work it is its originality/novelty: ,this thesis report is based on literature review, with no original contribution for the research. This study concludes by providing insights useful to future researchers for Industry 4.0 applications in the field of manufacturing.
In questo XXI secolo, le imprese manifatturiere stanno affrontando un numero crescente di sfide nella competizione del mercato globale. La selezione delle decisioni appropriate è un aspetto importante nel settore manifatturiero. È noto che la qualità delle informazioni disponibili per i responsabili delle decisioni è fondamentale per prendere decisioni. Pertanto, questo lavoro di tesi è volto a rivedere la letteratura disponibile nel campo del processo decisionale nel settore manifatturiero, identificando la ricerca sullo stato dell'arte e le lacune della ricerca, con l'identificazione di un modello generale di processo decisionale dal punto di vista dell'Industria 4.0. Una revisione sistematica della letteratura è stata fatta utilizzando parole chiave selezionate per cercare nel database SCOPUS al fine di analizzare la letteratura disponibile relativa al processo decisionale nella produzione dal 2012 al 2018. Un'analisi comparativa è stata fatta tra le diverse configurazioni del processo decisionale per sapere i pro e i contro dal punto di vista di Industry 4.0. Risultati: i documenti trovati, pubblicati su riviste e molte altre fonti, sono stati analizzati in modo descrittivo e brevemente trattati con particolare attenzione alle diverse configurazioni del processo decisionale. In particolare viene discusso l'implementazione di un modello decisionale a due stadi (livello superiore e livello base) sulle tre diverse configurazioni del processo decisionale, in termini di: a) numero di decisori coinvolti; b) obiettivo dei decisori; c) condivisione delle informazioni tra gli attori (cioè livello superiore e livello base); d) coordinamento tra i decisori. Ricerca e implicazioni pratiche: la qualità delle informazioni e il coordinamento delle decisioni sono importanti per prendere decisioni e con la giusta capacità di analisi possono migliorare le prestazioni dei sistemi di produzione. Poiché le tecnologie stanno crescendo rapidamente e ciò influenza il modo in cui vengono prese le decisioni. Pertanto, Industry 4.0 è un aggregato di tecnologia che ridefinirà il modo in cui la gestione e il processo decisionale vengono svolti in varie organizzazioni. Limitazioni: la revisione della letteratura è stata condotta raccogliendo i dati dai documenti disponibili dal 2012 al 2018, includendo solo la lingua inglese e la ricerca solo nei settori dell'ingegneria e delle scienze decisionali. Un altro limite era l'uso del solo database di ricerca SCOPUS. Una limitazione del lavoro è la sua originalità / novità: questo rapporto di tesi si basa sulla revisione della letteratura, senza alcun contributo originale per la ricerca. Questo studio si conclude fornendo informazioni utili ai futuri ricercatori per le applicazioni dell'Industria 4.0 nel campo della produzione.
Decision making in manufacturing from Industry 4.0 perspective
REPALLE, YOGA VENKATESH
2017/2018
Abstract
In this 21st century, manufacturing firms are facing an increasing number of challenges in the global market competition. The selection of appropriate decisions is an important aspect in the manufacturing sector. It is a well-known that the quality of available information for the decision makers is crucial in making decisions. Thus, this thesis work is aimed at reviewing available literature in the field of decision making in manufacturing, identifying the state of art research and research gaps, with the identification of a general model of decision making process from the perspective of Industry 4.0. A systematic literature review has been made by using selected keywords to search in the SCOPUS database in order to analyze the available literature related to decision making in manufacturing from 2012 to 2018. A comparative analysis was made among the different configurations of decision making process to know the pros and cons from the perspective of Industry 4.0. Results: The found papers, published in journals and many other sources, have been analyzed descriptively and briefly discussed with focus on different configurations of decision-making process. In particular it is discussed the implementation of a two stage decision model (top level and base level) on the three different configurations of decision making, in terms of : a) number of decision makers involved; b) objective of the decision makers; c) information sharing between the actors (i.e. top level and base level); d) coordination between decision makers. Research and practical implications: The quality of information and coordination of decisions are important for making decisions and with the right capacity to analyze can improve the performance of the manufacturing systems. As technologies are growing rapidly and that affects the way the decisions are made. So, Industry 4.0 is an aggregate of technology that will redefine how management and decision making are done in various organizations. Limitations: The literature review was conducted by collecting the data from the documents which were available from 2012 to 2018, by including only English language and searching only in the fields of Engineering and Decision Sciences. Another limitation was the use of only SCOPUS search database. One limitation of the work it is its originality/novelty: ,this thesis report is based on literature review, with no original contribution for the research. This study concludes by providing insights useful to future researchers for Industry 4.0 applications in the field of manufacturing.File | Dimensione | Formato | |
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2018_09_REPALLE_YOGA.pdf
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2018_09_REPALLE_01.pdf
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Descrizione: Decision Making in Manufacturing from Industry 4.0 Perspective
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https://hdl.handle.net/10589/142446