Model-Based Manufacturing System Supported by Virtual Technologies in an Industry 4.0 Context

Author(s):  
Vesna Mandic
2012 ◽  
Vol 457-458 ◽  
pp. 921-926
Author(s):  
Jin Zhi Zhao ◽  
Yuan Tao Liu ◽  
Hui Ying Zhao

A framework for building EDM collaborative manufacturing system using multi-agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous intelligent manufacturing system over Internet is proposed. According to the characteristics of agile EDM collaborative manufacturing system(AEDMCMS), the agent technology is combined with Petri net in order to analyze the model. Based on the basic Petri Net, the definition is extended and the Agent-oriented Petri net (APN) is proposed. AEDMCM is turned into the model of Petri Net which is suitable to the analysis and optimization of manufacturing processes.


Author(s):  
Lutz Lackner ◽  
Mats Larsson

In the production of green parts from powder, there is unavoidable slight deviation in the die filling, even when high-quality powders are used. The quantity of powder in the die varies and thus affects the weight of the compact. This filling variation results in variation of the pressing force, and thus influences the part geometry. The development of the DORST Netshape® System was conceived as an autonomous manufacturing system in order to compensate for these effects. Based on the Dorst Industry 4.0 innovations for part weight measuring immediately after pressing in combination with a laser dimension measuring system, this technology package attempts to reach enhanced precision and consistency in production. The paper presents results from various trials that show the capability of this new system, designed to improve the quality of pressed parts.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 12746-12754 ◽  
Author(s):  
Hao Tang ◽  
Di Li ◽  
Shiyong Wang ◽  
Zhijie Dong

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shailendra Kumar ◽  
Mohammad Asjad ◽  
Mohd. Suhaib

Purpose This paper aims to put forward a labelling system capable of reflecting the level of different Industry 4.0 (I4.0)features present in a manufacturing system and further propose a comparative index to collectively estimate and compare the system automation level. Design/methodology/approach Data for the empirical study were collected from interactions with the practising managers and experts. A relationship among the six I4.0 features is developed with fuzzy cognitive maps. Findings The paper proposed a simple and easy-to-understand labelling system for I4.0 systems, which indicates the automation level in each of six dimensions of any manufacturing system. The system is further strengthened by a proposed automation comparative index (ACI), which collectively reflects the automation level on a scale of “0” to “1”. Thus, the labelling system and parameter could help in comparing the level of automation in the manufacturing system and further decision-making. Research limitations/implications Only seven industrial sectors are illustrated in the paper, but the proposed concept of the classification scheme and ACI find their applicability on a large spectrum of industries; thus, the concept can be extended to other industrial sectors. Furthermore, a threshold value of ACI is a differentiator between a I4.0 and other automated systems. Both aspects have the scope of further work. Practical implications The way and pace by which the industrial world takes forward the concept of I4.0, soon it will need a labelling system and a parameter to assess the automation level of any automated system. The scheme assesses the automation level present in a manufacturing system. It will also estimate the level of the presence of each of all six attributes of an I4.0 system. Both labelling system and ACI will be the practical tools in the hands of the practising managers to help compare, identify the thrust areas and make decisions accordingly. Originality/value To the best of the authors’ knowledge, this is the first study of its kind that proposed the labelling system and automation comparison index for I4.0 systems.


Author(s):  
Megashnee Munsamy ◽  
Arnesh Telukdarie ◽  
Pavitra Dhamija

Logistics activities are significant energy consumers and known contributors to GHG emissions, hence optimisation of logistics energy demand is of critical importance. The onset of the fourth Industrial revolution delivers significant technological opportunities for logistics optimisation with additional benefits in logistics energy optimisation. This research propositions a business process centric logistics model based on Industry 4.0. A Logistics 4.0 architecture is developed comprising Industry 4.0 technologies and associated enablers. The Industry 4.0 architecture components are validated by conducting a Systematic Literature Review on Industry 4.0 and logistics. Applying the validated Logistics 4.0 architecture to a cyber physical logistics energy model, based on the digitalisation of business processes, a comprehensive simulation is developed identified as the Logistic 4.0 Energy Model. The model simulates the technological impact of Industry 4.0 on a logistics network. The model generates energy and CO2 emission values for “as-is” and “to-be” Industry 4.0 scenarios.


Author(s):  
Vikas Kukshal ◽  
Amar Patnaik ◽  
Sarbjeet Singh

The traditional manufacturing system is going through a rapid transformation and has brought a revolution in the industries. Industry 4.0 is considered to be a new era of the industrial revolution in which all the processes are integrated with a product to achieve higher efficiency. Digitization and automation have changed the nature of work resulting in an intelligent manufacturing system. The benefits of Industry 4.0 include higher productivity and increased flexibility. However, the implementation of the new processes and methods comes along with a lot of challenges. Industry 4.0. requires more skilled workers to handle the operations of the digitalized manufacturing system. The fourth industrial revolution or Industry 4.0 has become the absolute reality and will undoubtedly have an impact on safety and maintenance. Hence, to tackle the issues arising due to digitization is an area of concern and has to be dealt with using the innovative technologies in the manufacturing industries.


2019 ◽  
Vol 31 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Morteza Ghobakhloo ◽  
Masood Fathi

Purpose The purpose of this paper is to demonstrate how small manufacturing firms can leverage their Information Technology (IT) resources to develop the lean-digitized manufacturing system that offers sustained competitiveness in the Industry 4.0 era. Design/methodology/approach The study performs an in-depth five years case study of a manufacturing firm, and reports its journey from failure in the implementation of enterprise resource planning to its success in integrating IT-based technology trends of Industry 4.0 with the firm’s core capabilities and competencies while pursuing manufacturing digitization. Findings Industry 4.0 transition requires the organizational integration of many IT-based modern technologies and the digitization of entire value chains. However, Industry 4.0 transition for smaller manufacturers can begin with digitization of certain areas of operations in support of organizational core strategies. The development of lean-digitized manufacturing system is a viable business strategy for corporate survivability in the Industry 4.0 setting. Research limitations/implications Although the implementation of lean-digitized manufacturing system is costly and challenging, this manufacturing strategy offers superior corporate competitiveness in the long run. Since this finding is rather limited to the present case study, assessing the business value of lean-digitized manufacturing system in a larger scale research context would be an interesting avenue for future research. Practical implications Industry 4.0 transition for typical manufacturers should commensurate with their organizational, operational and technical particularities. Digitization of certain operations and processes, when aligned with the firm’s core strategies, capabilities and procedures, can offer superior competitiveness even in Industry 4.0 era, meaning that the strategic plan for successful Industry 4.0 transition is idiosyncratic to each particular manufacturer. Social implications Manufacturing digitization can have deep social implications as it alters inter- and intra-organizational relationships, causes unemployment among low-skilled workforce, and raises data security and privacy concerns. Manufacturers should take responsibility for their digitization process and steer it in a direction that simultaneously safeguards economic, social and environmental sustainability. Originality/value The strategic roadmap devised and employed by the case company for managing its digitization process can better reveal what manufacturing digitization, mandated by Industry 4.0, might require of typical manufacturers, and further enable them to better facilitate their digital transformation process.


Procedia CIRP ◽  
2020 ◽  
Vol 93 ◽  
pp. 32-37 ◽  
Author(s):  
Mandaná Moshiri ◽  
Amal Charles ◽  
Ahmed Elkaseer ◽  
Steffen Scholz ◽  
Sankhya Mohanty ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document