Thursday, February 6, 2014

Operations Innovation & Transformation – Fleet Management Part 4 of 5

by Stan Devries, Senior Director Solutions Architecture, Invensys|Schneider Electric

The 4 quadrants described in the article “Operations Innovation & Transformation – the 4 Types Part 1 of 5" positions the lower left quadrant as a strategy for using a “fleet” of physical assets in a new way.

In this quadrant, a group of similar industrial operations (2 or more) adapt their performance objectives, business processes and accompanying hiring and information strategies to optimize the “fleet.”  The move is to unifying the industrial enterprise over multiple sites (in groups or as a whole), with a more holistic view in terms of operating strategy and performance management.

This innovation can be limited by the distribution flexibility among the locations, but several corporations have achieved success with this.  One example is keeping most of the locations operating at a constant or “base” portion of the combined market demand, and using the more agile locations to deliver the “swing” or variable portion of the demand.  Another example is allowing all locations to serve their local markets without contribution from any other of the “fleet,” but they all adapt their operations to meet a shared performance objective, such as yield or efficiency.

A key method used to sustain this strategy is the increased automation of work.  This is a significant step beyond scorecards, dashboards or rigid workflows.  The following 2 examples show how real-time performance measures (different from traditional Key Performance Indicators, or KPI’s) and proactive procedural automation sustain this differentiation.
  •          A “fleet” of similar industrial operations have some distribution flexibility so that they can deliver a portion of each other’s market demand.  Each operation delivery point and each operating shift for that segment are benchmarked with the others, and all delivery points and their shift performance carry a real-time performance score.  Some delivery points are more agile, and some operator shifts have fewer errors than others (quality, over/under delivering, reworks).

  •          A “fleet” of similar industrial operations within a single location or nearby locations has distribution flexibility, but they only share in real-time benchmarking (such as efficiency) and online performance guidance.  The following is an example when all physical assets are used, with equal output at this point in time:

All of the physical assets share real-time benchmarking performance on efficiency and availability.  Now consider what can happen differently when supply or demand changes suddenly, such as an unplanned outage within the industrial operation or within a client’s operation:

In the left-hand diagram, losing capacity can cause all of the “fleet” to shut down, if fast and accurate guidance isn’t available and used to either import capacity (if feasible) or negotiate reductions in demand with one or more of the customers.

In the right-hand diagram, a client’s unplanned outage causes some or all of the “fleet” to operate in zones which might be unstable and trigger unplanned outages, if fast and accurate guidance isn’t available and used to either shut down one of the physical assets or export some of the product (at a discounted price).

Proactive procedural automation, using real-time performance measures and best practices, helps the fleet to sustain high reliability and better overall efficiency, yield etc.  It is used to present the decision makers (including operators) the business and operational alternatives and their consequences, in a simple form, such as the efficiency/yield/cost without changes and the corresponding performance if one of the alternatives is implemented in time to avert an unplanned outage or a significant shortfall in performance.  This does not require exotic technology, but it requires the implementation of trustworthy, on-line performance calculations and human workflows.

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