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Roadmap to Smart Manufacturing for Developing Countries
Published in Shwetank Avikal, Amit Raj Singh, Mangey Ram, Sustainability in Industry 4.0, 2021
Vaibhav S. Narwane, Rakesh D. Raut, Balkrishna Eknath Narkhede
Developing countries like India, Singapore, and Brazil etc. have started the adoption of smart manufacturing. Ang et al. (2017), Kamble et al. (2018), Luthra and Mangla (2018), Tortorella and Fettermann (2018) carried out adoption studies in developing economies. Two different studies carried out by Kamble et al. (2018) and Luthra and Mangla (2018) investigated barriers and challenges to smart manufacturing for Indian companies. Lack of clear understanding about the benefits of IoT and higher cost of implementation are major barriers for Indian manufacturers (Kamble et al., 2018). Luthra and Mangla (2018) list the barriers as lack of universal standards and protocol, absence of government policies and support, economic constraints, internet and infrastructure issues, and top management support. Original equipment manufacturers (OEMs) like ship manufacturers face challenges of strict environmental rules and customized needs of the customer. Ang et al. (2017) proposed a 2-way framework for ship design, operation, and manufacturing with smart design (space exploration, performance evaluation, geometry modification), smart operation (big data), and smart manufacturing (Cyber-Physical Meta-Models, integration Meta-Models). Tortorella and Fettermann (2018) studied the relationship between lean practices and I40 implementation for manufacturing firms in Brazil. Lean practices and adoption levels of I4.0 were categorized into low-level and high-level and improvements in operational performance were studied for the same.
Big Data Analytics for AV Inspection and Maintenance
Published in Diego Galar, Uday Kumar, Dammika Seneviratne, Robots, Drones, UAVs and UGVs for Operation and Maintenance, 2020
Diego Galar, Uday Kumar, Dammika Seneviratne
In industrial practice, many engineering systems have been designed by decoupling the control system design from the hardware/software implementation details. After the control system is designed and verified by extensive simulation, ad hoc tuning methods have been used to address modeling uncertainty and random disturbances. However, the integration of various subsystems, while keeping the system functional and operational, has been time consuming and costly. For example, in the automotive industry, a vehicle control system relies on system components manufactured by different vendors with their own software and hardware. A major challenge for original equipment manufacturers (OEMs) who provide parts to a supply chain is to hold down costs by developing components that can be integrated into different vehicles (Baheti & Gill, 2011).
DEFINE—An Architecture Framework for Designing IoT Systems
Published in Ricardo Armentano, Robin Singh Bhadoria, Parag Chatterjee, Ganesh Chandra Deka, The Internet of Things, 2017
OEM/ODM (Original Equipment Manufacturer/Original Device Manufacturer) parts are basically subsystems (products) which are bought as a subsystem and integrated into the products. Best examples in the case of IoT products are Power Supplies and Wireless modules. These are basically finished products manufactured by OEM/ODM vendors that can be used in designs. Although use of OEM/ODM parts reduces the design cycle, we need to remember that cost of OEM part will be more than the same designed part of the circuit. Other than parts like Power Supplies that need specialized skills, OEM/ODM parts make economic sense when the volumes are less, but expensive when the volumes are high. Another challenge that designers normally miss is the need for understanding the OEM/ODM part completely so that it can be successfully used the products. Most of the times designers miss the critical elements of the EOM/ODM part and product runs into trouble.
Dynamic inventory replenishment strategy for aerospace manufacturing supply chain: combining reinforcement learning and multi-agent simulation
Published in International Journal of Production Research, 2022
Hao Wang, Jiaqi Tao, Tao Peng, Alexandra Brintrup, Edward Elson Kosasih, Yuqian Lu, Renzhong Tang, Luoke Hu
The structure and dynamics of the aerospace supply chain (SC) significantly differ from many industries; for example, food or fashion (see Figure 1). The SC of the food industry has a linear material and information flow, with each participant taking on clearly-defined roles, such as material supply, manufacturing, distribution and/or retail. The aerospace SC is a more complex network where the functions and services provided by different participants are intertwined (Brintrup, Wang, and Tiwari 2017). With increased technology and product diversity, outsourcing has become the main source of labour specialisation and cost compression (Zhou, Zhu, and Wang 2020). Here, the Original Equipment Manufacturer (OEM) is the dominating factor responsible for part manufacturing, final-product assembly, and on-time delivery. The suppliers provide the remaining parts and raw materials. While the supply chain is typically configured to avoid both tardiness and reduce costs, the assembly process is often delayed by the late arrival of certain parts due to raw material shortage, limited resources, manufacturing defects and resultant repair/remanufacturing works. Participants in the SC might encounter understock, thereby causing a series of postponements that propagates along the SC and triggers the so-called ‘ripple effect’ (Dolgui, Ivanov, and Sokolov 2018).
Universal manufacturing: enablers, properties, and models
Published in International Journal of Production Research, 2022
The manufacturing equipment used by different companies is usually produced by a limited number of original equipment manufacturers (OEMs). A superset of manufacturing equipment across many companies would serve as a basis of universal manufacturing factories. A virtual factory would manufacture the products using the equipment produced by OEMs. Such a factory would exploit affinity among products, resources, processes, and services. A virtual factory would naturally offer more alternatives for product delivery, some of which could be more advantageous than the corresponding traditional company. The benefits derived from the virtual factory would be largely production related such as higher capacity utilisation, lower transportation costs, large production volumes, would offer benefits such as sustainability, resilience, and product personalisation.
Design of customised products and manufacturing networks: towards frugal innovation
Published in International Journal of Computer Integrated Manufacturing, 2018
The first tool of the developed framework is an augmented reality product customisation application. This application is published by the OEM, prior to entering a new market or when new products are to be introduced to an existing market, to capture the pulse of the targeted market. Utilising this tool, the OEM has a great advantage as the provided products are closer to customer needs; it permits the OEM to limit his manufactured product range solely to those asked mostly by the end users and also test customer opinion in newly introduced product designs. Additionally, through the developed mobile application, the customer becomes more intrigued to participate, as, through augmented reality, the result is highly realistic and close to the actual product. This information is crucial for expanding OEM’s network and provides products closer to customer needs in different regions.