How to master manufacturing’s data and analytics revolution
Manufacturing is on the verge of a data-driven revolution, but like all revolutions it will require the right actions, individually and collaboratively, to realise its full potential. Within a few years, manufacturers will collaborate in hyperconnected value networks in which data‑and‑analytics applications drive productivity, new customer experiences, and societal and environmental effects. Indeed, data and analytics are a key driver in realising the “Factory of Future” by enabling transparency, predictions and autonomous systems. Already today, we see leading manufacturers applying data and analytics to achieve their objectives for efficiency, sustainability and resilience. The imperative to boost efficiency and productivity is driven by intense cost pressures as well as liquidity issues arising from Covid-19 pandemic-related business disruptions. Sustainable operations are at the top of the agenda for many companies.. At the same time, they are seeking to build more resilient and connected supply chains, so they can anticipate and react faster to disruptions. Most companies recognise that data and analytics are rapidly changing the way they manufacture goods. Despite the high ambitions and strong value proposition, companies have not yet tapped the full potential. A triad of interconnected success factors Successful companies have demonstrated that three elements must be combined to drive full-scale implementation of data and analytics. First, they focus on value in selecting applications. Second, they establish a solid technological backbone comprising both information technology (IT) and operations technology (OT). Third, they promote organisational readiness to ensure that investments deliver the anticipated returns. Examples from various industry sectors demonstrate the importance of these success factors: Petrochemicals: A large petrochemical client of Schneider Electric is leveraging advanced process control to improve asset productivity and energy consumption in a highly complex integrated plant. The advanced process control is informed by an accurate digital twin based on a thermodynamic model. Moreover, effective visualisation […]