Integrated Condition Monitoring as a Business Model - A year in review…

It's hard to believe that it's been almost one year since I first set out to write this series of articles. While not as popular (and profitable) as J.K. Rowling's Harry Potter series (anyone with a pre-teen son or daughter will appreciate the reference), it has nonetheless been an enjoyable exercise. Many thanks for the continued requests for reprints, feedback, general support and most of all to Coxmoor Publishing for providing the forum. We'll begin with a short synopsis (quiz at the end)…

I began this quest by searching for the reasons why CM is not as fast a growing industry or practice, as many of us would believe it to be, or better yet, could be. In my first article I suggested that the problem is not with the tradeshows, economy, etc., rather with the implementation and acceptance of CM in general. I pointed to the lack of CM information being integrated within the enterprise and the 'decision support systems' used to sustain them. This lack of integration is unfortunately a two-way street, i.e. process and finance information are rarely an integral part of the CM program. Following this theme, I suggested that CM programs need to be measured by the same financial metrics used to quantify the process. In essence, I suggested that CM needs to be recognized as a value-added asset, differentiating the company, product or process through increased availability, yield and quality. Otherwise, I believe CM (and the maintenance organization in general) will remain a cost item subject to the cost-reduction cycle we are all too familiar with…

To clarify, I believe that just like a process variable is used to measure the process, CM data can be used to indicate the condition (Condition Indication) of a particular set of assets within the process. For example, I can envision a time when the Decision Support Systems (DSS) available to an operator will be able to accurately assess the condition of a specific asset. The result might be a simple red, yellow, green symbol next to the operator's MMI display. While the operator is never exposed to the underlying CM data, the Condition Assessment Systems (CAS) that are part of the DSS will be able to disseminate the information and aid the operator in the efficient and profitable operation of the process.

Of course building an integrated CAS and DSS system relies on 'open system' standards such as those being proposed by MIMOSA, OPC, etc. For example, the same system that provides an operator with a 'status' condition indication, also provides the ability to review all CM information collected across various platforms in order to make an informed analysis decision (as well as Root Cause Failure Analysis (RCFA), Equipment Lifetime Estimation, etc).  It also provides the rest of the enterprise system with the necessary information to make informed financial and economic decisions with regard to the overall business objectives of the company (not to mention health, safety and environmental impact). 'What if' scenarios can be developed to determine the real ramifications of shutting down a group of assets for routine or unscheduled maintenance vs. running the equipment to failure in order to meet a set of business objectives. Someday these 'real-time' decisions will be assisted with solid facts and alternatives. 

What is the best way to justify and measure the benefits of CM? In my last article I suggest EVA (Economic Value Added) as the answer. John Mitchell's paper on the Producer Value Model was the source for much of my information. EVA is simply the after tax profit (operating income less taxes and interest effects) of a company minus the cost of the capital required to produce the product. In this context, it can be shown how CM information affects a product's conversion costs (the cost to produce a product less raw material) and more importantly OEE (Overall Equipment Effectiveness). OEE is a normalized quantifier best describing the effects of product quality, production efficiency, and production availability. Obviously, by improving OEE through CM (and using OEE as a CM metric) one can effectively justify CM as a true asset to the organization. CM is the only practice that can affect both the OEE and Conversion Costs of a product. This has a doubly beneficial effect. By improving OEE (at the O&M level of the organization), the yield of a product is improved, thus improving the revenue potential of a product. By reducing conversion costs, the gross margin, or profitability of a product increases as function of this increasing revenue of the finished good. Everybody wins and the company is rewarded with an increasing EVA (real profit).

One company that I believe effectively communicates the importance of CM in terms of EVA and how it may be effectively integrated at the enterprise level is the DEI Group (http://www.dei-group.com), headed by Mr. Marton Dundics. Marton was one of the founding MIMOSA members, and last April made a presentation at the Annual MIMOSA Meeting in Scottsdale, Arizona titled 'A Common Denominator for Effective Exchange with CMMS Systems'. Marton clearly articulated the transition of CMMS systems into Enterprise Asset Management (EAM) Systems. In the presentation he produced Figure 1 which shows an actual information flow diagram from the perspective of CM information as it affects the Economic Value Added of a company.  

There are a couple of important aspects to this diagram: The first is the importance of the 'Corporate/Divisional/Plant Strategy' as an input to the RCM module. This 'outside' block is the heart of the company and what hopefully sets itself apart from the competition. Here the premise for a company’s RCM and CM philosophies are formulated. To emphasize the point, Marton references Figure 2, a Balanced and Linked Set of Metrics, from which the underlying metrics used in the DSS (the center block of Figure 1) are based. These are the metrics by which your CM program must respond and how you must communicate your results back to the organization.

The 'data block' is where all the CM and process variables are input to the system, both online and offline. The information is then 'fused' and archived for analysis by the Condition Assessment System (CAS). The RCM block is the interface to the Corporate Strategy noted earlier, and as such it sets the strategy whereby the Condition Assessment Module is based. Reliability can really be defined as the probability that a piece of equipment (or process) will perform in a defined satisfactory condition for a given time period. Condition Assessment, from a reliability perspective, is really a monitoring of failure modes and their respective symptoms to determine if a change in reliability has occurred.  The CAS system in the DEI module is providing this level of analysis by integrating all the CM information and using an 'inference' engine (knowledge based expert system, or even neural networks) to provide the analysis and results. 

This the second important aspect of Figure 1, the condition assessment information is translated and becomes the input for the two other modules within the DSS, the Economic Life Estimator and Economic Decision Management Modules. These modules determine the effect of an asset's condition in terms of EVA. This is also where the tie to the outside Financial Management Objectives, just like the Corporate Strategy input to the RCM Module, becomes crucial. All this information is 'output' to Production Control via what we know today as the CMMS, but as DEI and I believe will become the EAM system of tomorrow. Figure 3 shows a practical implementation of the flow diagram in Figure 1. 

Figure 1 clearly demonstrates the importance of intelligent DSS systems where RCM, CM and their links with the financial and corporate objectives of a corporation play an integral (an integrated) role in the future of tomorrow's Enterprise Systems. 

So now I have come full circle…Some have asked is all this really possible and is anyone implementing systems with measurable results? The answer is yes, and yes, but not enough. The companies who are beginning to recognize the financial reward of integrated CM are your traditional Enterprise, DCS and CMMS companies. So the CM industry's 'not dead yet' (Python pun intended), it's just going through a transition. 

In the future, I believe the provider of company wide DSS/CAS systems will not be the traditional CM companies we are familiar with today. Rather today's companies (after some consolidation) will become suppliers and partners to the larger DCS/Enterprise System suppliers of tomorrow. There will always be the techno toolbox market (data collectors, analysis software, etc.), but it will never reach the growth rate of the DCS and Enterprise provider. These companies spend more money on one product development effort than our entire industry spends on all its R&D combined. They have also done a much better job selling corporate wide business solutions to the executive level of an organization. 

Unfortunately, today many enterprise suppliers are simply providing 'links' to partner CM companies and advertising them as integrated. While the name on the box may sell the concept at the upper level, the implementation usually reveals the limitations. Therefore, it is up to the maintenance managers, RCM and TPM coordinators and the like, to clearly communicate the benefits of an integrated CM and DSS system. Once companies learn to recognize the economic value of integrated CM, and the way it can differentiate their company from the competition (Wall Street rewards companies for such benefits just look to TQM as an excellent example) will real change occur. For my fellow visionaries, I believe the next big paradigm shift in manufacturing, Enterprise and Equipment Asset Management is clearly visible. Is anyone in the financial markets listening - we're here when you're ready!

Chris Staller
ICM Technologies, Inc.
cstaller@icmtech.com

EVA is a registered trademark of Stern Stewart & Co.

Figure 1. Information Flow Model

Figure 2. A Balanced and Linked Set of Metrics

Figure 3. Integrated Condition Monitoring and Assessment System