Emerson Exchange 365

Quantitative Benefit Estimation Methodology for Measurement Devices

What is the economic value of a new measuring device in a process plant – a new analyzer, a more accurate flow measurement, an additional temperature or pressure measurement, etc.? Plant engineers are often presented with the issue of economically justifying new measurement in addition to those required to safely operate the plant and meet regulatory requirements.

Doug White at Emerson ExchangeEmerson’s Doug White shares a financially sound methodology that yields quantitative benefit estimates in his workshop at the Emerson Exchange 2017 conference.

Doug opened sharing a story of a recent plant visit where an engineer confided with him that he couldn’t convince the management team that he needed additional measurement devices to fix a steam balance problem. They wouldn’t listen. That was the genesis of this presentation to share ways to develop economic justifications for additional measurements.

Doug explored the plant decision cycles and evaluation of financial performance. The operating objectives of a plant are safety (zero safety incidents), sustainability (zero environmental incidents, excess energy used), availability/reliability and financial optimization. The question is how measurements impact these objectives.

The plant decision cycle—measure, analyze, predict, decide and implement and this cycle repeats continuously. The priorities and decision cycles revolve around these levers of financial performance:

Plant Decision Cycles

The question to answer is how an additional measurement impacts the profit side or the total capital side of the financial performance equation. How does additional measurement impact this equation? It can happen in several ways—increasing equipment capacity, reduced unplanned downtime, improve product quality, reduce energy consumption, reducing emissions penalties, etc.

Doug provided several case studies. The first example was to look at how measurement accuracy impacts business performance. Improved accuracy reduces the variability of the measurement and the ability to operate closer to the specification limit. The movement may mean higher throughput, quality or other characteristics that can drive price, cost and other financial levers.

In the case of the story of engineer who couldn’t convince management of the measurement, Doug showed an analysis of measurement instruments with 3% accuracy not being able to detect a leak on a statistical basis, but 1% accuracy could see the leak and estimate how large the leak is. This estimate could be translated directly into energy costs to use as the justification for the more accurate measurements.

He shared a more complex example in the value of using on-line analyzers to replace offline lab measurement results. The solution involved modeling the difference in times—4 hour updates for lab analysis versus 20 minutes for the on-line analyzer. The standard deviation of the loop drops when the loop can respond to disturbances more quickly. This allows the unit to run closer to the specification limit and improve the yields. Based on the specific operating conditions of the plant, these numbers can be translated into financial terms with a return on investment.