Operations Innovation & Transformation – Fleet Management

We saw the expansion of control system, operation system extending beyond the fall walls of plant(fixed plant), in mining, oil and Gas, and Food and Beverage, and a month into this year we have this trend growing. The challenge being placed is how can we bring, apply the same approach found on fixed plant to fleet, or mobile plant. This blog takes a look at the network of fleet management across plants, next week we need to move to mobile plant.

  

The 4 quadrants described in the article “Operations Innovation & Transformation – the 4 Types” 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 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).

Coordinators (different industries have different names for this function) use workflows to negotiate upcoming changes in demand and the operating shift and the coordinators use the same visual demand, using a “tram line” display.  Information to the right of the center dashed line is forecast and planned.

•          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).