China
Africa
Explore chapters and articles related to this topic
Production Management Methods
Published in Susmita Bandyopadhyay, Production and Operations Analysis, 2019
The dictionary meaning of the word “agile” is “nimble” or “swift.” Agile manufacturing is a type of manufacturing which responds to customers’ requests very quickly through the use of various tools, its processes, and required training. The term “agile” started to be used in manufacturing industry during 1990s. Thus the concept of agile manufacturing is almost two decades old. The main principles of agile manufacturing are: Organize to accommodate changeLeverage the effect of people and informationCooperate among each other in order to increase competitivenessEnrich the customer
Deposition-Based and Solid-State Additive Manufacturing Technologies for Metals
Published in Amit Bandyopadhyay, Susmita Bose, Additive Manufacturing, 2019
Initially, technologies to create three-dimensional (3D) components from computer-aided design (CAD) files have been termed as Rapid Prototyping technologies as these are primarily used to create prototypes of the parts with different materials, primarily plastics. However, there is paradigm shift from prototyping to direct manufacturing/production of 3D components and therefore these technologies have been improved over the last few decades and are being called as additive manufacturing (AM) technologies. Currently, the output of AM technologies include up to 20% final products and is estimated to increase to 50% by 2020 (The Economist 2011). While the invention of technologies is being argued to be a “Third Industrial Revolution” (The Economist 2012), huge investment and development efforts are required to fully realize their potential (Reeves and Hague 2013). The unique benefits of these agile manufacturing technologies include rapid production of components with efficient utilization of available resources, reverse engineering to develop functional components, new materials development such as light weight structures, complex integration of materials including assemblies with moving parts, functionally graded materials, etc.
Agile
Published in Terra Vanzant Stern, Leaner Six Sigma, 2019
Villiers describes Agile Manufacturing as tools, techniques and initiatives that enable a plant or company to thrive under conditions of unpredictable change. Agile manufacturing not only enables a plant to achieve rapid response to customer needs, but also includes the ability to quickly reconfigure operations—and strategic alliances—to respond rapidly to unforeseen shifts in the marketplace. In some instances, it also incorporates “mass customization” concepts to satisfy unique customer requirements. In broad terms, it includes the ability to react quickly to technical or environmental surprises. It is a means of thriving in an environment of continuous change, by managing complex inter and intra-firm relationships through innovations in technology, information, communication, organizational redesign and new marketing strategies.
Agile manufacturing: an evolutionary review of practices
Published in International Journal of Production Research, 2019
Angappa Gunasekaran, Yahaya Y. Yusuf, Ezekiel O. Adeleye, Thanos Papadopoulos, Dharma Kovvuri, Dan’Asabe G. Geyi
Over the years, companies around the world have been investing resources in improving efficiency, effectiveness and responsiveness of their manufacturing systems, including, for instance, Material Requirement Planning (MRP), and manual engineering techniques such as Total Quality Management (TQM), Just in Time (JIT) and continuous improvement (Inman et al. 2011; Karlsson 1996; Maskell 2001; Paranitharan and Jeyathilagar 2017; Yusuf 1996). However, challenges such as unprecedented instability may threaten the responsiveness of formal planning systems, which rely on historical data and a relatively high degree of market stability. Furthermore, manual engineering techniques such as TQM and JIT systems focused exceedingly on continuous improvement of internal work processes even as external change drivers required an equal amount of emphasis. Therefore, in order to remain competitive, manufacturers have been outward facing and ensure dynamic response to developments in areas such as technology, materials and customer preferences. In this regard, structures and systems for seamless exchange of information and knowledge on replicable designs and world-class competencies are inevitable. Agile manufacturing aims at helping companies to become more competitive and prosperous in challenging environments, where change is unanticipated and continuous (Dowlatshahi and Cao 2006; Gunasekaran, Subramanian, and Papadopoulos 2017).
Universal manufacturing: enablers, properties, and models
Published in International Journal of Production Research, 2022
Agile manufacturing implies flexibility at an enterprise level, and it is realised by creating processes, tools, and training to address changing customer needs. DeVor, Graves, and Mills (1997) defined agile manufacturing as the ability of a producer of goods and services to thrive in the face of continuous change. The paper offered as a summary of agile manufacturing research. Dubey and Gunasekaran (2015) defined manufacturing agility as an operational strategy to deal with uncertainties resulting from the worldwide economic recession, shortening of product life cycle, supplier constraints, and obsolete technologies.
Agile manufacturing practices: the role of big data and business analytics with multiple case studies
Published in International Journal of Production Research, 2018
Angappa Gunasekaran, Yahaya Y. Yusuf, Ezekiel O. Adeleye, Thanos Papadopoulos
Agile manufacturing stresses simultaneous excellence on a wider range of competitive metrics, especially being first to market with leading-edge solutions that surpass customer expectations and derail competitors’ plans, delivered at the cost of mass production (Fitzgerald 1995; Gunasekaran 1998; Adeleye and Yusuf 2006; Nandhakumar 2011). Agile manufacturing helps companies be competitive and thrive in environments where change is continuous and unanticipated (Sarkis 2001; Dowlatshahi and Cao 2006). Literature has highlighted the role of information technology as an enabler in agile manufacturing (e.g. Gunasekaran 1999; Yusuf, Sarhadi, and Gunasekaran 1999; Dowlatshahi and Cao 2006; Dubey and Gunasekaran 2015). In a recent study, Dubey and Gunasekaran (2015) suggest that agile manufacturing is inextricably related to the technologies that can share information effectively and efficiently, enabling organisations to improve dynamic sensing and speed (Elkins, Huang, and Alden 2004). Hence, technologies and information-sharing in particular are crucial for the achievement of agile manufacturing. With the advent of digital technologies, big data and business analytics (BDBA) came to the foreground as an important capability that enables companies to create value from an increasingly massive (and unstructured) amount of data, thereby gaining competitive advantage (Chen, Chiang, and Storey 2012). BDBA, according to Wang et al. (2016), comprises two elements: (i) big data and (ii) business analytics. The former term refers to the gathering and processing of data that has the qualities of velocity, variety and volume. The latter term has to do with applying the appropriate methods and techniques to enable decision-making. Within logistics and supply chain management, a number of recent studies have demonstrated the benefits of big data (e.g. Wamba et al. 2015; Wang et al. 2016; Hoffman 2017; Kim and Ahn 2017; Papadopoulos et al. 2017; Zhong et al. 2017) across different contexts, e.g. manufacturing (Jain, Shao, and Shin 2017), health sector (Wu 2017) and semiconductors (Wang and Zhang 2016). Others have suggested a positive link to firm performance (Ji-fan Ren et al. 2017) and to better decision-making (Tan et al. 2017). This new emergent work suggests that BDBA plays a major role in the agility of an organisation. It does so by providing timely and more accurate information about product demand (demand planning) and by quickly designing and developing an integrated supply chain network, product and process and collaboration among partnering firms. Moreover, BDBA helps in inventory control, transportation, scheduling and quality control at the operational level by having more accurate and timely information for making correct decisions in support of agility.