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How the MES alleviates electronics manufacturers challenges through better integration and connected orchestration.
Medical device manufacturers face a unique set of challenges where data and its management are concerned from an Industry 4.0 perspective.
A truly Industry 4.0-enabled semiconductor fab needs more than a MES. It needs an IoT data platform, which encompasses the core MES functionality, but has the capability to unleash the potential of IoT through enhanced data storage and manipulation capabilities.
The importance of harnessing large volumes data and the value its analysis creates has been the rhetoric behind Industry 4.0 and seen as one of the major drivers towards achieving the benefits associated with it.
MES applications which were pre-IIoT were mostly custom built, and many times ‘closed’ systems where business and product, logic and flow were intertwined and integration with enterprise applications was optional. You need to look at the current MES deployed in your process and ask the following five questions; upon answering them, it will become clearer whether or not an overhaul can save your application or it needs to go.
Are you deciding between an MES or an IIoT Platform? What about leverage them both? MES enables value chain-wide improvements, which no IIoT platform alone can ever achieve.
There is a lot of debate and discussion pertaining to the way a Manufacturing Execution System (MES) should function from an IIoT and Industry 4.0 perspective. The words ‘open’ vs. ‘closed’ application are also encountered in such debates; I will focus on the basic difference between an open and a closed MES, and which one is suited for the times to come.
Industry 4.0, Smart Factory, Digital Factory, Connected Enterprise, Factory of the Future, Plant floor to ERP, Convergence of IT & OT, IIOT and Digitization are either connected terms or very close to each other with slight differences.
As the data sources grow in size and variety, things get more complicated, and the Data Warehouse implementation projects become extremely long and prohibitively expensive, since they imply a normalization of all business data. But there are alternatives.
