In the current economic climate, only the strongest businesses are likely to survive. That means companies who perform reliably with a healthy cost level and, therefore, are able to build a competitive advantage over weaker performers. This also allows them to maintain a positive margin even in a depressed market, while others fall into red figures.
The road to better manufacturing performance is littered with well-meaning improvement efforts that fall short. In some cases, initial progress fizzles out due to a lack of structure and incentives. In others, the workforce never embraces the desired change, viewing it as a top-down directive rather than an initiative they can truly own. Although executives often recognize emerging issues that impede improvement, developing and executing strategies that effectively address those issues have proved to be a recurring challenge.
More specifically, without failure modes all you have is a bunch of codes. This may be the most overlooked data element as most computerized maintenance management system (CMMS) products do NOT capture the failure mode. This critical data element allows one to: (1) derive the ideal maintenance tactic, (2) quickly compare work order (WO) failure modes with RCM analysis failure modes, and (3) support drill-down on asset worst offenders for basic failure analysis. Failure data and failure analysis provide a holistic process in search of continuous improvement – using the CMMS. And, within the entire CMMS product, this may be the one feature’s greatest potential, return on investment.
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Spindles are one of the most expensive and sophisticated rotating components on the planet. They rotate at super high speeds with fits and tolerances 10 to 20 times what is required on other rotating devices, such as pumps or motors. If there ever were machines that needed to communicate their health and activity it would be spindles.
For some time, supermarkets have accepted that the costs for high customer volume, regulatory compliance and increasing energy rates were part of the business model. But the Danfoss Group, a Danish global producer of products and services used within infrastructure, food, energy and climate, has been providing a smart store solution for the past 10 years to help its customers across 5,000 stores worldwide optimize food safety and maximize energy efficiency. This solution also allows its customers to view their operations at a presentation level, create reports on alarms and performance, compare performance between stores, and reduce energy costs.
With all the technology out there, all talking to each other, the world is increasingly becoming more and more connected – indeed, flat. The Industrial Internet of Things (IIoT) seems like a nebulous concept that encompasses everything from machine learning and robotics to drone delivery systems and intelligent point-of-use vending. There is more information available than ever before, but making sense of all this data can be daunting. This article will help bring clarity to how the IIoT can enhance all aspects of manufacturing.
Let’s face it, most companies need a culture intervention – something like a 12-step program. This article will explore behavioral issues that are often at the core of a culture of neglect and mediocracy. It borrows much from management science, leadership principles and conversations with individuals working in the field of maintenance reliability.
It’s hard to think of another environment where an equipment failure could have an immense negative impact on employee safety and lost production than an offshore oil and gas production platform. Yet, offshore platforms are among the world’s most difficult locations to operate and maintain equipment. In most cases, skilled people and supplies can only reach the platform by ship or helicopter, so the cost of bringing technical specialists, replacement equipment, spare parts and tools to the platform is very high. On nearly every offshore platform, oil analysis plays a critical role in alerting the maintenance team to problems that have the potential to damage a vital system and providing information that makes it possible to efficiently allocate scarce resources by planning maintenance based on actual need as opposed to simple intervals of time.
This installment shows how the Bristol-Myers Squibb Company (BMS) aligned its central efforts with the reliability strategy. It continues the journey from Part 1 in Uptime’s December/January 2016 issue describing the initial implementation of Uptime Elements at BMS and Part 2 in Uptime’s February/March 2016 issue demonstrating how the sites began to adopt and utilize Uptime Elements as a communication tool to set strategy and align reliability efforts with their specific site goals. This seemingly hands-off approach helped to create an organic culture with a sense of ownership for the sites while still maintaining a consistent approach globally.
In today’s industrial environment, most turbomachinery has permanently installed machinery protection systems that incorporate vibration monitoring instrumentation. These systems typically utilize proximity probes to monitor both radial and thrust events (i.e., relative vibration measurements), case mounted seismic vibration transducers (i.e., absolute vibration measurements) and a shaft speed/phase reference measurement. By incorporating the preexisting machinery protection systems’ available measurement types into a routine vibration analysis program, technicians can determine specific fault types and machine condition based on signal amplitudes, frequency content and phase relationships between machine components. Additionally, these measurements can be acquired for machine commissioning purposes after mechanical repairs/inspections and utilized for machinery diagnostics with the use of multi-channel transient vibration analysis techniques.
The highly structured RCM process is a proven approach for determining what must be done to any physical asset to ensure it continues to do what you want it to do in the present operating context. The first step of the task selection process starts by assessing the effects of the failure mode and classifying them into one of four broad categories of consequences. The next step identifies a proactive task that reduces the consequences of failure to the extent that it is technically feasible. The criteria used to judge whether an on-condition maintenance task is technically feasible are fairly consistent across the various compliant RCM processes. Specifically, RCM2™ uses the following yardsticks:
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