Manufacturing companies are continually striving to achieve and maintain a high level of operational excellence. Operational excellence requires continual improvement of a company’s manufacturing operations, driving them to become increasingly lean and agile. To meet the goals of operational excellence, manufacturers must be able to fully utilize the information in all of their control and information systems. Achieving this level of utilization requires the ability to easily integrate these disparate control and information systems. Significant advances supporting these information exchange requirements have been made in recent years in the application areas of advanced process control, finite scheduling, asset management, statistical process control and supply chain integration. However the integration of Operations and Maintenance (O&M) related information has lagged behind these other areas of information exchange. This situation limits the opportunities to make important business operating decisions that are dependent upon integrated O&M information. In today’s world of interdependent supply chain partners and O&M outsourcing models, the limitations also have significant implications that reach beyond the bounds of any single enterprise into the extended enterprises they are part of with their various collaboration partners. In a more practical scenario, this problem could be easily represented by an unexpected equipment failure during the execution of a planned production order. It is clear that this is going to impact operations in the enterprise. However, that same impact is now propagating up and down the entire supply chain with potential financial implications including penalty costs and loss of business.

This document explains how three industry organizations, MIMOSA, the OPC Foundation, and the ISA’s SP95 Committee are working together to provide the process industries the capability to openly and securely exchange O&M information.

As today’s business environment of lean manufacturing sites, build to order manufacturing models, just in time delivery of parts and ingredients, and integrated supply chains combine to permit reduced inventory levels they also cause the cost of unexpected equipment failures to skyrocket. If an equipment failure causes a key part or ingredient to be delivered late or at diminished quality, an entire production run can be negatively impacted with a significant associated loss in profitability. In this context, failure includes any change in equipment performance resulting in unacceptably low production quantity or quality, as well as equipment performance resulting in unacceptably high safety risks, manufacturing costs or environmental impact.

Inventory can be used as a buffer to partially offset the risk of diminished production, but in the pursuit of operational excellence, this is a costly step backwards. The ability to anticipate and prevent unexpected equipment failures by performing maintenance based upon actual equipment condition information and operating parameters can lead to both reduced maintenance costs and lower equipment failure rates. It also enables superior operational decision making, since equipment availability forecasts will be more reliable, making production schedules more accurate. Enhanced Decision Support Systems (DSS), leveraging all enterprise information, are the key to managing these issues in an economically optimal manner.

The ability to perform maintenance based upon actual asset condition information is called Condition Based Maintenance (CBM). Using CBM related information along with other operating environment inputs to optimize operating decisions for an effective enterprise is known as Condition Based Operations (CBO). This document focuses on the use of CBO in process industries to enable more economically efficient production.

Condition Based Operations involves using current O&M information to make the best economic decision for the business. From the production operations management perspective, scheduled production is viewed as a time window (e.g. two shifts, one week) where production runs are scheduled on equipment, or assets. Production in a given time period is often constrained by equipment availability during the same time period. Production plans and detailed production schedules are created based upon planned maintenance schedules. Production plans and schedules are often disrupted by unplanned asset failures. In addition even the most careful maintenance planning usually only includes coarse input from operations and ongoing business requirements (e.g. critical and highly profitable orders on tight schedules).

The result of these lurking threats is that when a production schedule is issued the likelihood, or confidence in meeting it, decreases as ones looks further into the future. This loss of confidence (or reduced visibility) is at least partially a result of relying upon assumed, or unverified, inputs regarding asset availability to the scheduling process and not being able to accurately predict asset health and maintenance requirements during the schedule period.