PRODUCTION & OPERATIONS
that measurement process even more efficient and productive ?” he says , pointing to AI as a technology that could help in this arena , automating analysis and collection to save time and resources .
“ As an engineer , I ’ m constantly thinking about the process and effort that goes into anything we do .”
The benefits of capturing manufacturing data go beyond just enhancing productivity . Data has a vital role to play in operating and managing machines , enabling predictive maintenance , performance analytics and the futureproofing of vital systems .
NSK recognises this , which is why since 2006 / 7 the company has mandated that any new equipment and machines installed have to be data-driven and capable of data capture .
“ Instead of being reliant on verbal shift handoffs , notebook-driven transcription , or a dozen disconnected spreadsheets , we started a journey to more thorough , connected data and more relational processes for greater visibility ,” Jeremy says .
“ Now , we can draw better conclusions on connected data that captures what the machine is telling you and the observational human elements , joining these two things together for better KPIs and smarter decision making .”
This machine monitoring grows even more vital when we consider that NSK , like most manufacturers , has a mixture of legacy equipment and newer machines across facilities . Data has helped them strategically assess when to keep , retire and update machines , keeping cost impact and potential downtime low .
NSK ’ s solutions help create vital medical devices , like MRIs
“ Any replacement consideration starts by answering a basic set of questions – is the machine still working ? Is it operating with acceptable limits for performance / failure tolerance ?” Jeremy notes .
“ If so , we leave it in place , and many older machines are still monitored using paper processes and basic observations of performance with how often it ’ s in each state as a performance metric , as key points in the replacement decisionmaking process .”
Innovation here does not mean instantly updating every machine to the newest , swankiest model . For most manufacturers , this is not feasible with
90 November 2024