Reliability data drives decision making, reveals patterns and trends, and prevents asset failure. Gathering this data, however, is not always easy. Here are the top five sources for reliability data.

Reliability testing 

Reliability testing provides the most exhaustive life data for reliability. Companies can carefully control and monitor the collection of this data, and then use the information to successfully implement a reliability growth tracking program that will help leadership schedule, develop accurate cost projections, and plan the development cycle of future products. 

Sales and forecasting data

In order to understand the number of product failures in the field, the number of total units in the field must be accurate. This is where sales and forecasting data comes in. It provides you with an estimate on how many products are in the field at any given time so that reliability-oriented calculations can be made. 

Field service data

If handled correctly, field service data can be invaluable. It provides important information about failed products in the field. To make the most of this data, ensure that technicians sent out to physically repair products run a thorough failure analysis on all parts to determine which part specifically is responsible for the shutdown, record detailed failure information, use new units for replacement parts, and never take the “shotgun” approach to repair (replacing all parts for time instead of diagnosing the part responsible). 

Customer support data

Sometimes, it’s possible for customer support representatives to solve product problems over the phone by making a diagnosis and mailing out a replacement part, or if it’s a user issue, explaining to the user how to properly use the product. It’s recommended to keep this information in the same database as field service data as they can coincide. This information enables companies to understand how many of the problems are with their products because of actual failures, or client usability issues. 

Returned parts/failure analysis data

Failed parts or products that are returned provide important information about the reliability behavior of the product in the field. This information is especially valuable if technicians implement “shotgun” repairs as opposed to detailed failure analysis. For the most helpful data, the returned parts/products should be immediately analyzed to determine the cause of failure, and the findings should be linked to the field service records. This will provide the company with a holistic understanding of the nature of the failure to help prevent future warranty hits. 

Final thoughts

Because end-user consumers typically aren’t trained in the proper handling of products, it’s estimated that unreliability in the field will be two times what it was in the lab. Other variables contributing to this include transportation damage and manufacturing variations. This is where the discrepancy between in-house and field data comes in. Implementing the reliability sources above, however, will help companies monitor and analyze both sources of data and more accurately predict field performance from the results of reliability testing. 

About OptiAM®: OptiAM® EAM software is a secure, web-based application, designed to address unique customer requirements. Originally developed for the US Military by experienced maintenance personnel, OptiAM® is applicable to a wide range of asset types in any environment. Configurable and intuitive, OptiAM® applies to users in any industry.

About ASI: Andromeda Systems, Incorporated (ASI) is an ISO-9001:2008 company committed to superior technical performance and excellence in customer satisfaction. Our mission is to assist asset and fleet managers in achieving optimal levels of economy, availability, and safety by developing and applying leading systems engineering tools, processes, and expertise. We are headquartered in Virginia Beach, VA, with offices in Lexington Park, MD; Arlington, VA; Jacksonville, FL; Havelock, NC; Oklahoma City, OK and San Diego, CA.