8CIOReview | | NOVEMBER 2022IN MY OPINIONLEVERAGING THE POWER OF DIGITAL PROCESS AUTOMATIONBy Giovanni Di Stefano , Head of Innovation and Process Technologies, ComauThe increasing interconnectedness between production lines, industrial robots and complex manufacturing processes is one of the many benefits of digital automation. It is also empirically linked to higher productivity, faster time-to-market and lower costs. Today, digital process automation has evolved to incorporate everything from end-effectors and auxiliaries to individual product parts, allowing companies to create a digital twin of virtually anything that moves within the line. Furthermore, as everything is sensorized and talks to everything else, manufacturers now have access and insight as to the inner workings of singular components.Such real-time data, which is available, connected, analyzed and can be transferred throughout the organization, enables shared intelligence at a factory level that can reduce time to market by up to 25 percent; making digitalization a powerful tool in meeting challenging market conditions. For example, if we look at the development and deployment of a new line, digitalization allows an assembly cell to recognize small misalignments and reject potential design errors. This transfer of know-how, at an engineering level, enables the development of increasingly smart solutions. As the algorithms and process parameters combine to form a digital knowledge repository, the intelligence gleaned in one part of the line can be immediately applied to other applications or processes. Powerful analytics also enable more effective process control and a more complete vision of actual production flows and outputs. And because firms now have full access to interconnected, real-time data where and when it is needed ­ and in a form that can be easily and immediately interpreted ­ customized maintenance and process optimization is also possible.One of the challenges companies face in deploying digital automation strategies lies in understanding which data is fundamentally important and where to Giovanni Di Stefano
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