Additional Measurements and their Financial Impact

How Much Is Another Measurement Worth - Doug WhiteI continue to mine all the great presentations from the Emerson Exchange event in Anaheim last fall. Here is a recap of another one, How Much Is Another Measurement Worth?, by Emerson’s Doug White. You may recall Doug from many earlier posts on project justification and optimization.

Before beginning, I wanted to remind you that if you want to present at this year’s Emerson Exchange in Dallas, Texas (Sept 30-Oct 4), you have until March 18 to submit your presentation’s abstract.

Doug opened with an example of the value of information on checking our banking account balances. In the past, we received monthly statements and did manual updates to our check registers. Today, we have real-time access. This information potentially translates into cost avoidance from overdraft fees and revenue increases from moving funds to accounts with higher-paying interest to name a few examples. This extra information enables change but does not require it.

Plant engineers face the challenge to economically justify their projects. Doug highlighted some examples:

  • A new flow measurement that has a higher accuracy than the existing one or an additional one where none currently exists
  • A new measurement that might identify equipment problems earlier
  • A new online analyzer that replaces less frequent lab measurements
  • A more accurate temperature measurement in cases where precise temperature control is important

Doug shared the justification process as a series of questions that must be addressed. It begins with knowing what the typical plant objectives are. This feeds the question of what the typical plant decision cycles are. A separate question is how typical plants are evaluated financially. These separate questions converge with the question of how decision cycles impact plant financial performance. At the bottom level, most relevant to the plant engineer is how measurements impact decision cycles and financial performance.

The decision cycles in most plants with major influence on financial performance include in decreasing priority: process/equipment safety/shutdown, production/quality/process control, regulatory reporting, plant/equipment performance management, financial management, and logistics/production planning/scheduling.

Doug showed the levers to return on invested capital—composed of the profit side and the capital side. On the profit side, revenues can be impacted by the production rate and average selling price. Costs can be impacted by feedstocks, energy and utilities, and operating/maintenance/incidence costs. The capital side of the ledger is in what can be done to impact fixed and working capital.

Additional measurements in the production process can lead to an improved decision process, which leads to improved plant financial performance. Knowing better what the plant is currently doing implies more accurate and frequent measurements with less delay. Having this data provides what’s required for a model of comparison of now versus expected. It also provides the basis to predict the effect of alternative decisions.

The financial levers the plant engineer can impact in the area of increasing production rates include increasing equipment capacity, reducing unscheduled downtime, reducing scheduled downtime duration, reducing grade transition times, reducing batch cycle times, and reducing off-spec materials and waste.

On the price front, the lever is to increase the yield of the most valuable products and improve product quality. We’ve spent many posts on ways to address the cost side in managing energy usage, emissions, and maintenance costs.

Take a look at the presentation to see two case studies that Doug provides—leak detection and improving pump performance. In each case, the justification ties back to the financial levers so it’s important to understand these first and write your justification with these in the forefront.

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  • Anand Radhakrishnan

    Excellent article on how availability of more frequent, accurate, actionable data can increase productivity and plant efficiency along with reduced maintenance costs and plant downtime. Further all of this can lead to improved bottomlines for process plants.

    • http://www.linkedin.com/in/JimCahill Jim Cahill

      Thanks for sharing your thoughts, Anand!