Discuss About The Management Approached Production Internet.
Many innovative technology and software has change the face of the factory production and despite of that many critical challenges are being faced by the industries in the production sectors. Sustainability has become one of the most concerning subject for the current world and may approaches have been proposed such as AMS (Agile Manufacturing System) and FMS (Flexible Manufacturing System) among which, MAS has become the more emphasizing one. Automatic production system has been developed through the application of the WSN (Wireless Sensing Network), Internet of Things, Cloud Computing, and many more in manner to operate the CPS (Cyber Physical System) automatically (Schmidt et al. 2015). This report presents a literature review on how Industry 4.0 can be used as an opportunity within the industries for improving the existing system. The first section describes about the system architecture and operational mechanism of the industry 4.0, followed by which a comparison has been presented against the industry 3.0. This report also emphasizes on the challenges and opportunities of the Industry 4.0 over the existing technologies.
Lee, Jay, Behrad Bagheri, and Hung-An Kao (2015) expressed Industry 4.0 as a name for the trending and innovative technologies being implemented for the automation of the production processes and data exchange. It has also represented as the fourth industry revolution or smart factory that can take decentralised decisions through monitoring and creation of the physical processes within the cyber-physical systems (kang et al. 2016). Following is the figure describing the system architecture of the industry 4.0 describing the four tangible layers including supervisory control terminal layer, industrial network layer, cloud layer and physical resource layer:
This figure describes how the CPS is being execute through the exchange of the information and integration between the information exchange and the operation with the physical objects (Wang et al. 2016). Operational mechanism can be described as following design principles:
Interconnection: Lee, Kao and Yang (2014) stated, “Wireless communication technologies are playing prominent role in the enhancement of the internet access throughout everywhere in the world. Common communication standards play crucial role in the connection between the devices, machines, people, and sensors between all these entities. These standards can be helpful in allowing the flexibility connection between the vendors and the modular machines that can be alternatively resulting in the flexibility adaption approaches for the Industry 4.0’s Smart Factories (Schuh et al. 2015).
Information Transparency: A new picture of the information transparency can be enabled through enhancing the interconnection between the people and the objects and fusing both the approaches within each other. Considering this aspect, it is Important the participants connected via IoT are well informed with the results related to the data analytics related to the technologies associated among the participants (Brettel et al. 2014). Examples such as drawings, electronic documents and simulation models can be related to the information from the virtual world.
Decentralized Decisions: According to (Hermann, Pentek and Otto 2016) the combination of the decentralized and interconnected decision makers allowing the utilization of the global and local information at the same moment for enhancing the overall productivity and better decision-makings. Technically, it can stated that decentralized decisions can be enabled through the CPS as the embedded actors, sensors, and embedded computers are responsible for allowing the control and monitor over the physical world autonomously.
Technical Assistance: It is crucial factor for the humans for getting support from the assistance systems as the CPS has been making decentralized decisions and forming complex networks that led to the enhancement in of complexity in the production sector (Gorecky et al. 2014). It is a crucial factor for the robots to interact intuitively and smoothly along with the counterparts of the humans, in manner to successful, effective, and safe support of the human beings within the physical tasks involved in the human-machine collaboration.
In Industry 3.0, production means have been already interconnect ted with the reasonable automation level however; current technologies in the Industry 4.0, the automations through current technologies have been established in a predefined hierarchy manner. In this solution, inside factory (connectivity levels) have been already defined including the measurement of the process state through the sensors and software those have been utilized for the decision makings related to the logistics or planning. Drath and Horch (2014) eexplained the same concept through the statement, the vision of Industry 4.0 can be a helpful approach for the establishment of a hyper-connectivity that resulting in the wider scope even outside the factory boundaries. Following is the list describing the fundamental difference between the Industry 3.0 and Industry 4.0:
Cloud Differences: Previously, data was not being shared effectively among other organizations and employees however; further implementation enhances the scope for the data access that enhanced the supply chain management alternatively resulting in the enhancement of the performance of the organization.
Big Data and Analytics: Many data is being collected and has been increasing rapidly and that was enhanced through the big data implementation that allows the industries to analyse a sheer amount of data at instances.
Data collection: Industry 4.0 “enables other applications that can optimize overall equipment effectiveness, improved predictive maintenance, energy management etc. (Zhou et al. 2015).”
IoT implementation: Iot resulted in the better and effective communication between both the ends that can be helpful in utilizing the machinery devices in better and precise manner (Gilchrist 2016). It allows the user to feed data along with the feedback opportunity that alternatively results in the enhancement of the communication.
Opportunities of the Industry 4.0 can be divided between two perspectives including the micro and macro perspective of the industry 4.0 that can be clearly described as follow:
Business Models: In manner to offer new services, new business models can be much effective through the utilization of the smart data. Business models based on the ‘sustainability’ theme are capable of reducing the impact and creating positive impact fir the community and rest of the globe that can be utilized for eliminating the social or environmental problems (Liao et al. 2017). This can be an innovative approach for selling the tangible products only despite of selling separately the accessibility and functionality of the products.
Value Creation Networks: Industry 4.0 can be an approach for the realization of industrial symbiosis and product life cycles’ closed loop through the application of the value creation networks’ cross – linking properties. It can be helpful in allowing the efficient and effective coordination between the energy, material, water flows, and products in the different factories and the overall product life cycle. Following figure describes the Industry 4.0’s macro perspective:
Equipment: Retrofitting can be a better approach for enabling the cost – efficient and easy manner for upgrading the actuator systems and the exosting manufacturing equipment related to the sensors including the control logics that will be helpful in overcoming the equients’ heteroginity in factories (Shrouf, Ordieres and Miragliotta 2014).
Humans: Industry 4.0 provides three different approaches for the sustainability that can be utilized in manner to cope up with the social challenges those are being faced in Industry 4.0. this includes the implementation of the ICT technology for the enhancement in the training efficiency, enhancing the fostering creativity and intrinsic motivation through establishing the better approaches for the CPS (Kagermann 2015). Thirdly, enhancement in the extrinsic motivation though the implementation of the flow theory’s concept.
Organization: Koch et al. (2014) explained in relation with this topic that the major focus of the smart factory is to allocate the water, energy, materials, and products in effective and efficient manner through considering the CPS’s dynamic constraints.
Process: This desig can be an helpful approach towards addressing the Industry 4.0’s resource efficiency approach through using new technologies or designing the effective manufacturing process chains for exampe internally cooled tools and many more.
Product: Another concerning topic in the Industry 4.0, in relation with the sustainable design is to concentrate on the “realization of closed-loop life cycles” in manner to allow the product reusability through the application of the cradle-to-cradle (Stock and Seliger 2016). Following figures decrribes the Industry 4.0’s Micro Perspective:
With the continuous advancement in the Industry 4.0, interaction behaviour have been changing and so new challenges arise those can be listed as following:
Conclusion
Based on the above literature review, it can be concluded that Industry 4.0 has been a revolutionary approach towards the implementation of a sustainable environment and smart factories within the industries. New implemented features are innovative, effective, and efficient from the previous approaches. Various modifications and advancements have been implemented on the previous models such as Industry 2.0, and Industry 3.0 those could be utilized for far more application than it was earlier. This literature review presented the system architecture of the Industry 4.0 along with the design principles that can be helpful in clearing the concepts related to the Industry 4.0 and deep understanding on it. A comparison has been presented in this literature review considering the advancement and enhancement implemented within the industry 3.0 that separates it from the Industry 4.0. There are many opportunities associated with the Industry 4.0 is the possible technology that can enable the flexibility within the existing system and thus, reflect in the overall production and output of the organization. This report also throws light on the several challenges those are considerable with the sector of the Industry 4.0 and its proper and effective utilization within the real world.
References
Brettel, M., Friederichsen, N., Keller, M. and Rosenberg, M., 2014. How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 Perspective. International Journal of Mechanical, Industrial Science and Engineering, 8(1), pp.37-44.
Drath, R. and Horch, A., 2014. Industrie 4.0: Hit or hype?[industry forum]. IEEE industrial electronics magazine, 8(2), pp.56-58.
Gilchrist, A., 2016. Industry 4.0: the industrial internet of things. Apress.
Gorecky, D., Schmitt, M., Loskyll, M. and Zühlke, D., 2014, July. Human-machine-interaction in the industry 4.0 era. In Industrial Informatics (INDIN), 2014 12th IEEE International Conference on (pp. 289-294). IEEE.
Hermann, M., Pentek, T. and Otto, B., 2016, January. Design principles for industrie 4.0 scenarios. In System Sciences (HICSS), 2016 49th Hawaii International Conference on (pp. 3928-3937). IEEE.
Kagermann, H., 2015. Change through digitization—Value creation in the age of Industry 4.0. In Management of permanent change (pp. 23-45). Springer Gabler, Wiesbaden.
Kang, H.S., Lee, J.Y., Choi, S., Kim, H., Park, J.H., Son, J.Y., Kim, B.H. and Do Noh, S., 2016. Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(1), pp.111-128.
Koch, V., Kuge, S., Geissbauer, R. and Schrauf, S., 2014. Industry 4.0: Opportunities and challenges of the industrial internet. Strategy & PwC.
Kölsch, P., Herder, C.F., Zimmermann, V. and Aurich, J.C., 2017. A novel concept for the development of availability-oriented business models. Procedia CIRP, 64, pp.340-344.
Lee, J., Kao, H.A. and Yang, S., 2014. Service innovation and smart analytics for industry 4.0 and big data environment. Procedia Cirp, 16, pp.3-8.
Lee, Jay, Behrad Bagheri, and Hung-An Kao. “A cyber-physical systems architecture for industry 4.0-based manufacturing systems.” Manufacturing Letters 3 (2015): 18-23.
Liao, Y., Deschamps, F., Loures, E.D.F.R. and Ramos, L.F.P., 2017. Past, present and future of Industry 4.0-a systematic literature review and research agenda proposal. International Journal of Production Research, 55(12), pp.3609-3629.
Schmidt, R., Möhring, M., Härting, R.C., Reichstein, C., Neumaier, P. and Jozinovi?, P., 2015, June. Industry 4.0-potentials for creating smart products: empirical research results. In International Conference on Business Information Systems (pp. 16-27). Springer, Cham.
Schuh, G., Gartzen, T., Rodenhauser, T. and Marks, A., 2015. Promoting work-based learning through industry 4.0. Procedia CIRP, 32, pp.82-87.
Shrouf, F., Ordieres, J. and Miragliotta, G., 2014, December. Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm. In Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on (pp. 697-701). IEEE.
Stock, T. and Seliger, G., 2016. Opportunities of sustainable manufacturing in industry 4.0. Procedia Cirp, 40, pp.536-541.
Theorin, A., Bengtsson, K., Provost, J., Lieder, M., Johnsson, C., Lundholm, T. and Lennartson, B., 2017. An event-driven manufacturing information system architecture for Industry 4.0. International Journal of Production Research, 55(5), pp.1297-1311.
Wang, S., Wan, J., Zhang, D., Li, D. and Zhang, C., 2016. Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Computer Networks, 101, pp.158-168.
Zhou, K., Liu, T. and Zhou, L., 2015, August. Industry 4.0: Towards future industrial opportunities and challenges. In Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on (pp. 2147-2152). IEEE.
Zhou, K., Liu, T. and Zhou, L., 2015, August. Industry 4.0: Towards future industrial opportunities and challenges. In Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on (pp. 2147-2152). IEEE.
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