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Industry 4.0: Opportunities and Challenges for Turkey
Published in Kaushik Kumar, Divya Zindani, J. Paulo Davim, Digital Manufacturing and Assembly Systems in Industry 4.0, 2019
Hakan Erkurt, Özalp Vayvay, Elif Yolbulan Okan
In the white goods sector, sensors installed in parts, lines, and equipment will provide communication systems between machine-to-machine (M2M) and machine-to-human (M2H). The fact that end-to-end processes become more connected with each other will make production lines more agile and compatible. Vertical integration of in-house systems will increase efficiency of the production lines. Enterprise resource planning (ERP) systems will work in integration with product life cycle management (PLM) and other manufacturing systems (MES/MOS). Companies will respond to changing conditions by gathering detailed information from three system. Workforce productivity on the production floor will increase thanks to autonomous transport vehicles and shipping robots. These tools and equipment, which will work in coordination with each other, will provide timely delivery of parts and materials to the target using real-time data gathered from ongoing operations. The transport vehicles will be able to move on the production floor with the laser guidance system and communicate with other vehicles using wireless networks. Shipment robots will automatically find and select the appropriate materials for the next production run.
The origins of BIM in computer-aided design
Published in Ray Crotty, The Impact of Building Information Modelling, 2013
Thus, the big players have tended to focus on product lifecycle management (PLM), vendor-speak for systems needed to solve the problems associated with the enormous quantities of documents generated by people using CAD systems. PLM systems combine aspects of CAD modelling with document management, facilities management and geographical information systems, to enable the manufacturers of complex products and the owners of major facilities to manage their assets throughout their life-cycles. In some cases these efforts extend to integration or other linkages with corporate enterprise resource planning (ERP) systems. The mainstream vendors are also trying to address the challenge of collaborative working, concurrent engineering, model sharing, or whatever, generally over the internet, and generally using web browsers.
PLM Using IIoT Use Case
Published in Uthayan Elangovan, Product Lifecycle Management (PLM), 2020
PLM helps enterprises to take a cohesive, holistic view of their products and product-related processes that results inefficiency improvements,development of new products,reduced costs,increase in productivity, andimproved quality of products.
AI-readiness and production resilience: empirical evidence from German manufacturing in times of the Covid-19 pandemic
Published in International Journal of Production Research, 2022
Christian M. Lerch, Heidi Heimberger, Angela Jäger, Djerdj Horvat, Frank Schultmann
Hence, for enabling human-machine collaboration in manufacturing processes, companies first have to adopt the basic techniques for scheduling work instructions using digital solutions directly on the shop floor (Villalonga et al. 2021). Mobile devices like tablets are the prerequisite for this (Guhl, Tung, and Kruger 2017; Morkos et al. 2012). If one considers manufacturing as a comprehensive system of various activities and processes, it is hard to imagine its effectiveness without an Enterprise Resource Planning (ERP) system combined with Product-Lifecycle-Management (PLM) and process data management (Kakouris and Polychronopoulos 2005; Erkayman 2019). Moreover, smart manufacturing requires the further integration of cyber-physical systems enabling real-time control of all activities relevant to production and logistic/supply chain (in-bound and out-bound) processes (Drobot 2020; Modgil, Singh, and Hannibal 2021; Wolf 2009; Villalonga et al. 2021). Also robotic systems including mobile, collaborating and autonomous robots play a significant role for smart manufacturing on the shop floor level and are included in our dimensions (Stanescu et al. 2008). Finally, the essential foundation for AI is represented in real-time data availability and a high IT security (Baryannis et al. 2019; Dogru and Keskin 2020; Jöhnk, Weißert, and Wyrtki 2021), creating our sixth dimension.
Personal protective equipments (PPEs) for COVID-19: a product lifecycle perspective
Published in International Journal of Production Research, 2022
Shubhendu Kumar Singh, Raj Pradip Khawale, Haiyong Chen, Haolong Zhang, Rahul Rai
What can we do to alleviate the problem of the acute exigency of PPEs in pandemic crises? What can we learn from the current pandemic that can inform responses to future crises concerning PPEs How do we develop a structured process that provides a system-level approach for tackling the PPE exigency problem? This perspective paper's strong focus is to answer the questions posed above by focussing on initiating a system-level thinking process, particularly for policy, strategic, and tactical planning purposes. System thinking principles can act as a core to organise knowledge in issues related to PPEs. Product lifecycle management (PLM) is a system-level framework that focuses on managing and controlling entire product development, manufacturing, maintenance, and support processes all the way through until the product is retired or disposed of. A PLM based system-level thinking process is adhered to in the outlined paper. Next, we motivate why a PLM-based system thinking process is a required and reasonable approach for tackling the PPE exigency problem.
A systematic literature review to explore traceability and lifecycle relationship
Published in International Journal of Production Research, 2020
Angelo Corallo, Maria Elena Latino, Marta Menegoli, Pierpaolo Pontrandolfo
As widely recognised in the literature, the PLM approach provides several benefits to complex product industries, such as the improvement of the strategic processes, the improvement of the innovation capabilities, the reduction of cost or the shortening of the time to market. In this paper we argued that the PLM approach can play a key role in the food industry in which complexity characterise the value chain rather than the product. In such industry the PLM approach enables traceability, which is useful for food safety. Similarly, other industries might benefit from PLM, even if not characterised by complex products. Thus, it is reasonable, for the production research community, to investigate which industries have the greater potential to benefit from the PLM approach. With respect to this research route, we propose the following research question: ‘Which are the drivers for the PLM approach adoption in industries not characterised by complex products? Are such drivers linked with the complexity of specific industry features?'