Manufacturers in process industries are no strangers to raw material price volatility. Historically, price fluctuations of 15 to 20 percent have been common and threatened only the weakest companies. But when prices surge by 100 to 200 percent over the course of 12 to 24 months, the rules of the game change. And when those increases become systemic—not just cyclical—they threaten the viability of all processors– large and small. And that’s exactly where the industry finds itself today.

For decades, maintenance professionals have advocated and used information management systems, planned maintenance activities, emphasized preventive maintenance and assessed equipment utilization to eliminate non-essential assets (reducing numbers of equipment). These professionals also have been aware of the need for operator and mechanic training and, to some extent, decentralizing asset responsibility. Accordingly, they have been striving to build operator-ownership of equipment through basic care.

One of the major European postal services decided in the late 1990s to make a change in their plant maintenance organization. In my own U.S. Postal Service, there had been talk for years of combining the operations and maintenance supervision and reducing the supervisory ranks. It is easy to say, but how do you do it? Be careful of what you wish for!

The following paper will describe a methodology for automatically detecting and diagnosing rolling element bearing wear. The techniques involved have been proven in over 15 years of use in a huge variety of environments, machine types and applications. The techniques involved in diagnosing bearing wear will be described in detail and supported by a set of example graphs and an annotated diagnostic report.

There is still some controversy regarding the various certification levels, test questions and test procedures. These problems will hopefully be worked out in the future. However, despite these issues, certification is probably the glue that will be required to bind and network this group of analysts together in today’s dynamic job market.

This paper presents a case study in a process industry that illustrates how industrial productivity may be increased and business objectives achieved by application of a process termed as REU (Reliability of Equipment Usage). REU basically concentrates on the process of improving operational reliability through knowledge workers. Operational reliability may encompass problems in equipment, process, system, spare parts, cost, purchase, material stocking and a host of other problems connected to business effectiveness. The process is briefly described. The results and benefits of such improvements are highlighted.

Who is to blame when a defect occurs? Is it the supplier who was contracted to produce a key component or supply materials, or is it the customer organization that created the specs and produced the final product? As more companies outsource parts of production and develop closer partnerships with key suppliers, finding blame can topple the delicate balance in even the best customer-supplier relationship.

Savvy professionals in safety, quality, maintenance and reliability have long recognized that human performance analysis could be a bonanza for opportunities to improve and control operations. This article describes and explains a new approach to human factor analysis, an approach that provides a repeatable process and a practical methodology that can be used immediately by working professionals to deal with unwanted human behavior in the workplace.