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Aerospace production management
Published in Wesley Spreen, The Aerospace Business, 2019
Related to this effort, Industrial Engineering also creates tooling designs for the manufacturing operations, and designs the factory lay-out. The tool designs are sent to the Tooling department for fabrication, and the lay-out plans are sent to Facilities, which begins work preparing the physical manufacturing space. Industrial Engineering also develops a manpower estimate for the work to be performed and passes this estimate to Human Resources, which takes action to assure that sufficient manpower will be available, establishes a hiring plan if necessary, develops a training plan, and writes syllabi for training courses. Workers who have completed training and have received certification report to the factory for job assignments.
Influence of Assembly Automation and Market Factors on Production Economics
Published in Anoop Desai, Aashi Mital, Production Economics, 2018
In the face of increasing global competition, manufacturers are continually forced to look for ways to improve productivity. This has now become a dire necessity instead of just a passing fancy. It is evident that factory automation is revolutionizing global manufacturing. The increasing role played by automation in manufacturing operations is clearly evident. Automation is now all pervasive. It is not confined merely to manufacturing operations. An ever increasing number of industries have automated their material handling, assembly, and subassembly operations as well. The rise of artificial intelligence (AI) technologies has revolutionized entire industries. One of the major difficulties confronting engineers lies in the basic design of their products: products are either not designed for automated assembly or are poorly designed.
SmartCAM
Published in Paul W. Ross, The Handbook of Software for Engineers and Scientists, 2018
Digital computers are the key to computer-aided manufacturing (CAM) as well as computer-aided design (CAD). The objectives are to use computers to automate and control all manufacturing operations to increase productivity, reduce cost, and achieve high-quality products. Computers have been used for more than 30 years in continuous and discrete manufacturing operations. Applications included (Bedworth, 1991): product testing and quality control, foundry control, numerical control equipment interface, nuclear reactor control and monitoring, utility plants start up and control, and automobile assembly lines. Computer-aided manufacturing is not just a computer software that is used to generate codes for numerical-control (NC) machines or to simulate the operation; it is a philosophy of operation that requires complete understanding of the capabilities and functions of the manufacturing process to be automated and controlled (Bedworth, 1991; Chang et al., 1991; Amirouche, 1993).
The role of lean information flows in disaster construction projects: exploring the UK’s Covid surge hospital projects
Published in Construction Management and Economics, 2023
Cheng Wu, Naomi Brookes, Christine Unterhitzenberger, Nancy Olson
The concept of lean, which was initially utilized in manufacturing operations, aims to identify and eliminate all non-value-added elements from an activity to build a value stream for its effective delivery (Hines et al.2004). This concept has now also been applied to the general construction sector to eliminate unnecessary elements in the project delivery process to improve efficiency (Green 1999). Applying lean information flow is a relatively new area of research endeavour, which derived from lean information management (Hicks 2007, Hölttä et al.2010). Lean information flow aims to eliminate and avoid communication waste to ensure the flow is efficient (Redeker et al.2019). We posit that applying lean information flow in disaster project management may provide a useful lens through which to consider and improve disaster project delivery. Our research question, therefore, is as follows: “What role does lean information flow have in the effective delivery of disaster construction projects?”
The significance of digital waste in the automation of Lean practices
Published in Quality Management Journal, 2023
Industry 4.0 offers technologies for product improvement and innovation of manufacturing operations. It is important not to dismiss the focus on smart products through simulation, additive manufacturing, and augmented reality (Powell et al. 2018). One example of a smart product is 3 D printing. It appears early in a product’s life cycle, and it is the foundation for building multifunctional structures as smart products with integrated sensors in the manufacturing process chain (Lenz et al. 2020). Big data analytics, additive manufacturing, and sustainable smart manufacturing technologies are beneficial to manufacturing enterprises to make better decisions for the beginning-of-life stage of the product life cycle (Majeed et al. 2021; Yang et al. 2021).
Operation twins: production-intralogistics synchronisation in Industry 4.0
Published in International Journal of Production Research, 2023
Mingxing Li, Daqiang Guo, Ming Li, Ting Qu, George Q. Huang
Industry 4.0 with emerging technologies, such as Artificial Intelligence (AI) (Russell and Norvig 2003), Cyber-Physical Systems (CPS) (Lee 2008), Internet-of-Things (IoT) (Ashton 2009), Cloud Computing (Armbrust et al. 2010), Big Data Analytics (LaValle et al. 2011), Digital Twin (DT) (Grieves 2014) and many other related technologies, are revolutionising the way that how manufacturing operations are managed and done (Olsen and Tomlin 2020; Guo et al. 2020a). This revolution promises next-generation manufacturing with enhanced flexibility, increased resilience, and improved sustainability at a reduced cost, driving manufacturing practitioners to reevaluate their current manufacturing planning and control strategies to gain more competitive advantages. For example, the production and intralogistics (PiL) operations within traditional manufacturing planning and control strategies are organised separately by different departments, therefore, resulting in uncoordinated organisation and operations between the PiL (Li, Guo, and Huang 2021). The mismatch of PiL can generate workstation starvation/overload and unreasonable worker waiting/idling time, prolonging the overall manufacturing progress (Schmid and Limère 2019). Besides, uncertainties in the real-world such as uncertain failures of equipment, uncertain operational times, uncertain arrival of urgent jobs, keep disturbing the manufacturing systems and deteriorating the production performance (van der Zee 2013; Huo, Zhang, and Chan 2020; Jiang et al. 2021). From the viewpoint of systems thinking, PiL in a single factory are inherently coupled and interact with each other, which needs integrated organisation and operations throughout the entire PiL process. Moreover, a flexible and resilient strategy is indispensable for attenuating the cascading effects of uncertainty in the PiL process. Recently, the reflections on manufacturing planning and control in the context of Industry 4.0 provide promising insights into the conceptions of synchronisation of the PiL, which attracts widespread attention from both researchers and practitioners (Chankov, Hütt, and Bendul 2016; Zhang et al. 2018; Zhang et al. 2020; Pan et al. 2021a; Guo et al. 2021a; Li, Guo, and Huang 2021).