A single source of truth will transform how manufacturers compete and operate, though only a few are implementing at scale as yet, says Marcos Kauffman at the Institute for Advanced Manufacturing and Engineering

Marcos Kauffman

Blockchain technology is the key to unlock a number of new business models in manufacturing. Models such as machine as a service (MaaS) where instead of selling production equipment, a machinery builder can charge a manufacturer for its use and for its output. For example, instead of selling a 3D printer, the machinery provider can sell time on that machine or the volume produced. This approach reduces the upfront investment, improves levels of use and results in a better return on the asset. However, to realize such benefits, manufacturers must advance use cases beyond the pilot phase and improve their understanding of the technology. A recent Capgemini report shows that only 3 percent of organizations are implementing blockchain on a large scale. For end users, the roadmap to substantial adoption of blockchain technologies depends on a critical mass of skills and capabilities. Future academic research will focus on the development and testing of more complex business models, such as MaaS, which can facilitate documentation management, performance tracking and IP management. A single version of the truth will be distributed and authenticated across the value chain, automating use and payment for machines and services in smart contracts. The full potential of blockchain depends on our ability as academics and industrialists to bridge the skills gap through collaboration, overcoming challenges such as the traceability of complex products, the integration of value chain systems, data sharing, adherence to quality and process standards, and IP protection. ▪ Dr Marcos Kauffman is director of the Institute for Advanced Manufacturing and Engineering (AME) at Coventry University. His full article on blockchain, skills and new manufacturing models appears in ‘Growing with blockchain: from disruptive potential to operational reality’, Novaro Publishing, June 2020. See here for details.