scholarly journals Product Segmentation and Sustainability in Customized Assembly with Respect to the Basic Elements of Industry 4.0

2019 ◽  
Vol 11 (21) ◽  
pp. 6057 ◽  
Author(s):  
Branislav Micieta ◽  
Vladimira Binasova ◽  
Radovan Lieskovsky ◽  
Martin Krajcovic ◽  
Luboslav Dulina

Sustainable manufacturing is not just about manufacturing, but also products and services. In the area of custom production processes, there may also be circumstances of organizational management where compliance with labor productivity and the due-date principle is problematic. Similar products with different operating times cause the throughput of assembly lines to slow down, increase number of works in progress (WIP), and increase productivity waste. It is possible to reduce this impact through various productivity-enhancing methods and innovations. This paper presents an innovative approach to product segmentation in the assembly phase of custom manufacturing, and a proposal for a new segmentation procedure that will allow significantly better integration of products into existing assembly processes without negatively impacting the company’s production indicators. The scientific problem was defined on the basis that extending existing segmentation by the third dimension of operating times allows products in MTO (made to order) environments to be divided into families with approximately equal operating times. This will increase assembly efficiency in existing medium to large companies without large investments in the development and adaptation of assembly process products. The contributions of this work relate mainly to simple adaptations to existing processes in medium-sized businesses. The proposed solution respects the basic elements of Industry 4.0.

Author(s):  
Ravinder Kumar

A formal industrialization commenced with steam power generation and the application of machines that mechanized the industrial work in past. Subsequently, the development in electric power, the assembly lines, and mass manufacturing led toward the third era of numeric control and automation. Now in modern era of industry 4.0, robots connected with the computers and machines. Tools are working on machines learning algorithms and running the cyber physical manufacturing systems. Sensing the need of hour, Indian manufacturing organizations are working hard to implement the practices of Industry 4.0. Working on identical direction, the author has identified 12 enablers poignant the espousal of Industry 4.0 in Indian manufacturing sectors from literature review and by opinion of experts. Further, the author has used Decision Making Trial and Evaluation Laboratory (DEMATEL) technique for developing the structural and circumstantial kinship among the enablers of Industry 4.0.


Author(s):  
Ravinder Kumar

A formal industrialization commenced with steam power generation and the application of machines that mechanized the industrial work in past. Subsequently, the development in electric power, the assembly lines, and mass manufacturing led toward the third era of numeric control and automation. Now in modern era of industry 4.0, robots connected with the computers and machines. Tools are working on machines learning algorithms and running the cyber physical manufacturing systems. Sensing the need of hour, Indian manufacturing organizations are working hard to implement the practices of Industry 4.0. Working on identical direction, the author has identified 12 enablers poignant the espousal of Industry 4.0 in Indian manufacturing sectors from literature review and by opinion of experts. Further, the author has used Decision Making Trial and Evaluation Laboratory (DEMATEL) technique for developing the structural and circumstantial kinship among the enablers of Industry 4.0.


2019 ◽  
Vol 6 (2) ◽  
pp. b8-b13
Author(s):  
I. Karabegovic ◽  
E. Karabegovic ◽  
M. Mahmic ◽  
E. Husak

In the world of global competition, customers have increasing demands that companies must meet in order to remain active in the global market. For this reason, it is necessary to use new technologies in the production processes, i.e. to implement Industry 4.0. In other words, we need to create a connected company through the digital transformation that enables production processes to discover new ways to increase productivity and improve overall business performance. Companies need to get involved and start a digital system, and from supplier to customer. It is a key to the hidden value that can contribute to the company’s productivity, compliance, profitability, as well as the quality of the finished product, and eventually the introduction of flexible industrial automation of production processes. The aforementioned technologies and Internet of Things connect the physical and virtual world with a purpose to better collect and analyze data, transforming them into information that reaches decision-makers. To do this, it is necessary to implement smart sensors that provide information at all times. The implementation of Industry 4.0 in production processes is unthinkable without smart sensors and provides the following: faster product development time, lower overall costs, improved use of production processes and their optimization, as well as company risk management. The paper will outline the motives for the implementation of smart sensors and applications of smart sensors in production processes. Keywords: production process, smart sensor, Industry 4.0, production automation, digital transformation, flexible automation.


2019 ◽  
Vol 27 (1) ◽  
pp. 23-28 ◽  
Author(s):  
Erika Sujová ◽  
Helena Čierna ◽  
Iwona Żabińska

AbstractThe paper addresses application of digitazation of production processes, which is part of organizational digitization, also known as Industry 4.0. It deals with modernization and optimization of production systems by creating models in simulation software via digital engineering. For our analysis, 8 real assembly lines were used, with an average of 15 workplaces, which were integrated into one universal line by means of simulation. The aim of our research was to create a digital twin of the real assambly lien and to analyse effectiveness of the proposed modernization universal assembly line using the generated statistical data.


2008 ◽  
Vol 1 (2) ◽  
pp. 103-115
Author(s):  
Yinzhi Lai ◽  
Lina Wang ◽  
Ke Cheng ◽  
William Kisaalita

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