First of all, the enterprise is faced with equipment downtime and a decrease in productivity, which, according to ISA, can range from 5% to 20%. In some industries, this decline is equivalent to losing millions of dollars in profits.
In the long term, equipment failures can result in delays in order fulfillment and deterioration of business reputation, additional costs for unscheduled repairs, and even a threat to the life and health of personnel.
In such circumstances, it is critically important for an enterprise to develop and implement a systematic approach to dealing with failures. In other words, learn to manage failures by extracting potentially useful experience from negative situations.
This is exactly what such a direction as Failures Reporting Analysis and Corrective Action System (FRACAS) does. This failure management strategy is divided into three successive steps:
— Reporting (detection, identification and classification of failures);
— Analytics (research of failures in the context of the history of failures and maintenance plans);
— Correction (a set of measures to eliminate the consequences and prevent failures).
This is a fairly generalized interpretation of FRACAS. Behind it lies the work that is individual for each enterprise, directly related to technological limitations and features of the organization of business processes.
In world practice, there is a sequence of steps that can help create a failure management strategy from scratch:
However, there is no one-size-fits-all solution, and finding an effective and cost-effective solution will require a detailed study of each step of FRACAS.
Identification and classification of failures
Early detection of the problem can greatly reduce the cost of eliminating its consequences. At this stage, it is important to consolidate the efforts of all stakeholders. From operators and supervisors on the shop floor who are the first to encounter problems, to production planners and maintenance staff who can provide wiggle room if a problem is detected in a timely manner.
It is important to understand that relying only on the human factor, it will be difficult to achieve the necessary level of coordination of efforts. Therefore, for a successful failure management strategy, you will have to create an appropriate IT infrastructure.
Thus, the deployment of solutions based on the Industrial Internet of Things (IIoT), Artificial intelligence (AI), Digital Twin and other technologies of the Industry 4.0 category increases the speed of collecting operational data and their accuracy.
SmartEAM has solutions for remote equipment condition monitoring, anomaly analysis and failure prediction.
The choice of tools is individual for each enterprise, but it is worth remembering that the means of detection, identification and classification should be easy to use for all participants in the process. Otherwise, the failure management strategy will remain only a formality, stalling at the data collection stage.
When the process of collecting and primary processing of operational data is established, you can begin to interpret them. At this stage, it is important to provide a comprehensive analysis of information, examining failures in terms of causes and consequences, cost-effectiveness of maintenance, and the role of equipment in generating value.
Consider some of the possible areas of analytics:
Failure Mode and Effect Analysis. Analysis of potential risks and assessment of the consequences of detected failures for all business processes of the enterprise. The results of the study are a rating on the basis of which a practical management strategy is built.
Failure Code Creation. In-depth classification of failures with assignment of categories and prioritization depending on the severity of the consequences. Facilitates coordination of efforts to identify and eliminate problems. It is also the basis for automating failure management processes.
Root Cause Analysis. Root cause failure analytics to help you learn more about the sources of potential production problems. By separating symptomatic manifestations from real triggers and fundamental errors in the organization of processes, it is possible to develop effective measures to prevent failures.
Work Order Analysis. Analysis of the list of work tasks of the maintenance and repair service and statistics on closing applications allows not only to obtain objective information about the effectiveness of maintenance processes, but also to develop an optimization plan.
The needs of the enterprise dictate the introduction of other, alternative methods of analytics. At the stage of research and collection, you can additionally detect problems with excessive or insufficient financing of maintenance and repair, evaluate the efficiency of supply and inventory management, identify points of growth in the quality of processes or opportunities to reduce costs.
Maintenance strategy adjustment
The practical side of FRACAS helps to develop and implement a set of measures to eliminate failures and prevent them in the future.
Most of the actions at this stage should be aimed at improving the efficiency of maintenance and repair management. World practice demonstrates the growing popularity of proactive methods. And this is no coincidence, because Predictive Maintenance (PdM) and Prescriptive Maintenance (RxM) help to reduce the number of failures and equipment downtime.
And yet, proactive methods allow you to extend the life of assets, ensure an increase in overall equipment efficiency (Overall Equipment Effectiveness, OEE) or optimize maintenance and repair processes according to the required KPIs.
And this is no longer just a fight against failures, but a controlled impact on the economic success of production. In this way, the banal thesis “learn from your mistakes” can take on a real form, providing tangible benefits for the business.
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