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Author's profile photo Stefan Weisenberger

OEE, OxE and shifts competing for the best run – Impressions from the SAP Manufacturing Industries Forum 2015

A long day full of impressions from the SAP Manufacturing Industries Forum in Chicago – a clear highlight was IDC’s Bob Parker presenting today on digital transformation and IOT. He talked about OmniExperience – customer experience beyond commerce, Worksource – dynamic workforce when you need it with the qualification you neeed (not necessarily on your payroll, though), and the transformation of the “operating model”.

All of these are trends that fit well what I took away from customer conversations in mill products.


Much of these are still visions & ideas, rather than established business models – but the direction is clear. The transformation to the digital mill products will

include multichannel customer experience, a flexible blend of internal and external workforce, and companies interwoven in business network – and IOT.

IOT_Building_Blocks.PNG In our Mill Products customer panel discussion, as well in the interactive IOT session yesterday, we discussed building blocks for industrial IOT.


Connected Manufacturing and Connected Assets are the most obvious IOT use cases in our industries, and they are very closely connected (pun intended).


The foundation for Connected Manufacturing

The foundation for both are “integration” and “analytics. Bob Parker highlighted OEE as a good starting point. He actually made a point to go beyond OEE (overall equipment effectiveness), and also measure the effectiveness of a complete production line, a plant, and even across plants – thus calling it OxE. The math behind the KPI remains the same.


How do you get OEE? Well, SAP OEE based on SAP MII is a great starting point. Tim Day, Manager Manufacturing Systems at Johns Manville, explained how they build their journey to IOT on SAP MII. Manufacturing analytics from SAP MII are the discussion basis for operations meetings on plant level, and across plants – and the same real-time figures are available to the shop floor personnel. SAP MII based KPIs provide the basis to identify new best practices, and even make teams compete for the best run.


Empower the shop floor

I remember at least 2 customer examples in the forest products industries that go beyond OEE, and use integration to provide financial figures like real cost and profitability to the shop floor. The profitability of a mill is often won or lost on the shop floor. Operator decisions strongly influence yield, scrap, material consumption and target parameter adherence. Giving them better analytics and insight into the overall impact of decisions to the mill – I’d say this is real empowerment.


We had a side discussion whether this visibility into the performance of lines and plants is “tolerated” or “welcome” in the plant. Depending on company culture, country and unions this transparency might also be considered a threat. There is a lot of operational and organisational transformation needed, to enable such empowerment, I am afraid.


Tim brought up a great example: Imagine a customer request a specific quality parameter. In production you ensure that this parameter is not violated – practically you operate in a range between upper and lower value. If you are able to run production very precisely close to the target value ( and thus not overdeliver on quality (and cost)) – you save money. The tricky bit is to run more precisely, and closer to the edge.


Reliable real-time analytics (and a great manufacturing team) can make a lot of difference here. Add predictive capabilities to react faster on possible quality deviations, and you can push the limit even further.


Predictive OEE?

While listening to Bob Parker explaining the calculation of OEE – based on up-time and reliability (or quality), I scratched my head. We use the same predictive capabilities (although different sensor readings most likely) to calculate predictions on asset failure and quality issues. With SAP MII and SAP HANA we can even use the same toolset. Shouldn’t we call this predictive OEE, then? Or do you have better name?


Wanted – OEE and profit in one KPI

By the way, I am still looking for a good term to link OEE and profit. Any suggestions are highly welcome.
OEE in itself just tells me uptime and quality – but not for which product and with which profit. This has 2 aspects:
1) Imagine you have 2 products with different profitability that you could manufacture on the same equipment. OEE doesn’t help you in this. It only talks about quality and uptime.

2) In our industry, assets often fail gradually. So you may be able to still run the equipment – you either may produce the lower profit product at full quality and run rate, or the higher profit product at lower quality and run rate. Also in this case OEE is not really helpful.


If you have something better than OEE, please let me know. I would be happy to learn about it.

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