Without such a tight and near real-time integration, there is much anxiety and frustration within any enterprise that is in search of a more competitive, profitable, safe, and agile factory. How can any manufacturing company reduce non value-adding administration and empower their workforce to take immediate remedial actions?
Namely, the typical current state of affairs from the perspective of a senior vice president (SVP) of operations could be summarized as follows:
1. On one hand, the ever more pressured manufacturing environment demands acceleration of the stock-keeping units (SKU) mix and shorter lead times, all due to ever more demanding and fickle customers; but
2. On the other hand, the real world situation is of little overall enterprise and/or SKU-level profit visibility, and the company has to rely on (suboptimal) average key performance indicators (KPIs), with emergency scheduling (constant firefighting) on paper or Excel documents.
In such “clueless” environments, there are “blind spots” everywhere in terms of determining yields and losses, hidden capacity opportunity, and masked process routing and constraints by reactive work practices. Also, there are increased risks of quality non-compliance leading to manual quality assurance (QA) processes, whereas continuous improvement efforts are floundering and remain unmeasured. In a nutshell, the hands-on plant people do not seem involved and are ironically not accountable for what they should be.
The future state should logically be the inverse of the above, and the usual “first remedial step conclusion” is to gather the glut of data from data historians and MES databases, and then decide what to do. But, without smart and intuitive plant applications that have visualization and contextual business intelligence (BI) capabilities (and that are thus accepted by the plant staff), this will all be yet another exercise in futility.
The reality check reveals an “inconvenient truth” that many MES investments fail to deliver hoped for performance management outcomes due to people issues. Namely, after 18 months or so, the embattled company in case might have an overall equipment effectiveness (OEE) dashboard that the plant engineers occasionally look at (and which might have cool colors on it), but without a pervasive effect (actionable info) and acceptance across the plant (and entire enterprise).
Namely, the typical current state of affairs from the perspective of a senior vice president (SVP) of operations could be summarized as follows:
1. On one hand, the ever more pressured manufacturing environment demands acceleration of the stock-keeping units (SKU) mix and shorter lead times, all due to ever more demanding and fickle customers; but
2. On the other hand, the real world situation is of little overall enterprise and/or SKU-level profit visibility, and the company has to rely on (suboptimal) average key performance indicators (KPIs), with emergency scheduling (constant firefighting) on paper or Excel documents.
In such “clueless” environments, there are “blind spots” everywhere in terms of determining yields and losses, hidden capacity opportunity, and masked process routing and constraints by reactive work practices. Also, there are increased risks of quality non-compliance leading to manual quality assurance (QA) processes, whereas continuous improvement efforts are floundering and remain unmeasured. In a nutshell, the hands-on plant people do not seem involved and are ironically not accountable for what they should be.
The future state should logically be the inverse of the above, and the usual “first remedial step conclusion” is to gather the glut of data from data historians and MES databases, and then decide what to do. But, without smart and intuitive plant applications that have visualization and contextual business intelligence (BI) capabilities (and that are thus accepted by the plant staff), this will all be yet another exercise in futility.
The reality check reveals an “inconvenient truth” that many MES investments fail to deliver hoped for performance management outcomes due to people issues. Namely, after 18 months or so, the embattled company in case might have an overall equipment effectiveness (OEE) dashboard that the plant engineers occasionally look at (and which might have cool colors on it), but without a pervasive effect (actionable info) and acceptance across the plant (and entire enterprise).
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