Smart manufacturing

By Andrew Kusiak. International Journal of Production Research, 2018

797 citations recorded by the source corpus.

Manufacturing has evolved and become more automated, computerised and complex. In this paper, the origin, current status and the future developments in manufacturing are discussed. Smart manufacturing is an emerging form of production integrating manufacturing assets of today and tomorrow with sensors, computing platforms, communication technology, control, simulation, data intensive modelling and predictive engineering. It utilises the concepts of cyber-physical systems spearheaded by the internet of things, cloud computing, service-oriented computing, artificial intelligence and data science. Once implemented, these concepts and technologies would make smart manufacturing the hallmark of the next industrial revolution. The essence of smart manufacturing is captured in six pillars, manufacturing technology and processes, materials, data, predictive engineering, sustainability and resource sharing and networking. Material handling and supply chains have been an integral part of manufacturing. The anticipated developments in material handling and transportation and their integration with manufacturing driven by sustainability, shared services and service quality and are outlined. The future trends in smart manufacturing are captured in ten conjectures ranging from manufacturing digitisation and material-product-process phenomenon to enterprise dichotomy and standardisation.

Subfields: Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/d93d4b8a821a6761341fa9ace16b0e3a2ab232c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Industrial and Manufacturing Engineering

In Safety, Risk, Reliability and Quality

Citations in the corpus

Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations (2020, background): “The future of supply chain digitization will be driven by big data predictive analytics capability, powered by artificial intelligence (O’Leary, 2013; Loebbecke and Picot, 2015; Zhong et al., 2016; Kusiak, 2018; Ivanov et al., 2016, 2019b; Baryannis et al., 2019; Tortorella et al. 2020).”
Artificial intelligence in business: State of the art and future research agenda (2020, background): “Smart manufacturing, with its roots dating back to the works of Kusiak (1990; 2018), represents integrated systems that respond in real-time to the demand of the factory, the supply network, and the customer.”
Literature review of Industry 4.0 and related technologies (2018, neutral): “Both Kusiak et al. (2010) and Francis and Kusiak (2017) studied predictive models, neural networks, autoregressive integrated moving average.”
Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing (2019, background): “Currently, many conceptual frameworks, such as cloud manufacturing (Adamson et al. 2017) and smart manufacturing (Kusiak 2018), have been developed to provide an insight into the intelligent manufacturing paradigm.”
The internet of things for smart manufacturing: A review (2019, background): “The “ smartness ” level depends, to a great extent, on data-driven innovations that (Kusiak, 2017; Smart Manufacturing Leadership Council, 2018): enable all information about the manufacturing process to be available whenever it is needed, wherever it is needed, and in an easily comprehensible form…”
A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing (2019, background): “Digital technologies do not only enable data-driven decision support tools [39], but also stimulate the development of new production forms, such as smart manufacturing and Industry 4.0 [9, 40, 41, 42, 43].”
Sustainable manufacturing in Industry 4.0: an emerging research agenda (2019, methodology): “…2014), Integrated Industry (Bürger and Tragl 2014), Factory of the Future (Heynitz and Bremicker 2016; Liao et al. 2017), Smart Industry and Smart Manufacturing (Dais 2014; Wiesmüller 2014; Kusiak 2018) are also used to address similar requirements and are subsumed by the concept of ‘Industry 4.0’.”