Improving manufacturing process development

14 December 2020

Optimisation of the engineering chain by using digital twins looks like a very promising area to find improvement opportunities, according to Piotr Siwek, head of product marketing EMEA, Factory Automation at Mitsubishi Electric.

Optimising the entire engineering chain is becoming ever more important. Since the potential performance and availability of machines, in terms of overall equipment effectiveness (OEE) management, are already being effectively utilised, there is a need to search for competitive advantages elsewhere. 

Mitsubishi taken this approach in its Nagoya Works factories, where it has investigated the potential benefits of this approach in multiple areas. For example, by linking data between various engineering tools, it has reduced the design time for new applications. It could also decrease the time necessary for the physical implementation of digitally designed systems and could cut the maintenance time needed for existing assets.

While developing these solutions Mitsubishi has learnt a great deal about the potential areas of improvement in manufacturing facilities. An example of this in practice today is the use of software by engineers to perform mechatronics and structural debugging on newly designed production processes. Equipment is verified and results are instantly fed back to designers. In this way vast amounts of data, using the right methodology, can enable the continuous improvement processes. 

As a result, the start-up period for new production activities on some sites at it Nagoya Works, which includes on-site verification and the process of starting machines, has been reduced by 40%. 

When it comes to maintenance, the company has implemented several similar technologies. For example, it has developed a solution that is able to record equipment abnormalities in a new way. It is possible to see information on the behaviour of various components in combination with video streams of a whole machine or crucial process components. This gives a better understanding of what could happen on-site. These data are used as input information for design and simulation software, which enables and speeds up the improvement of machine design. 


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