Machinery Lubrication

Machinery Lubrication - Reliable Plant - Anniversary Edition

Machinery Lubrication magazine published by Noria Corporation

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GROUP PUBLISHER Brett O'Kelley - bokelley@noria.com EDITOR-IN-CHIEF Natalie Blythe - nblythe@noria.com SENIOR EDITORS Jim Fitch - jfitch@noria.com Bennett Fitch - bfitch@noria.com CREATIVE LEAD Patrick Clark - pclark@noria.com MANAGING EDITOR Breanna Moll - bmoll@noria.com EDITORS Josh Couch - jcouch@noria.com TECHNICAL WRITERS Wes Cash - wcash@noria.com Bennett Fitch - bfitch@noria.com Paul Farless - pfarless@noria.com Travis Richardson - trichardson@noria.com Jeremie Edwards - jedwards@noria.com GRAPHIC ARTISTS Matt Berkenbile - mberkenbile@noria.com Spencer Beeson - sbeeson@noria.com ADVERTISING SALES Peggy Tinsley - ptinsley@noria.com MEDIA PRODUCTION COORDINATOR Sheryl Adekoya - sadekoya@noria.com CORRESPONDENCE You may address articles, case studies, special requests and other correspondence to: Editor Machinery Lubrication Noria Corporation 1328 E. 43rd Court • Tulsa, Oklahoma 74105 Phone: 918-749-1400 Fax: 918-746-0925 Email address: editor@noria.com SUBSCRIBER SERVICES: The publisher reserves the right to accept or reject any subscription. Send subscription orders, change of address and all subscription-related correspondence to: Noria Corporation, 1328 E. 43rd Court, Tulsa OK 74105-4124. 918-749-1400 or Fax: 918-746-0925 Copyright © 2023 Noria Corporation. Noria, Machinery Lubrication, Reli- able Plant and associated logos are trademarks of Noria Corporation. All rights reserved. Reproduction in whole or in part in any form or medium without express written permission of Noria Corporation is prohibited. Machinery Lubrication is an independently produced publication of Noria Corporation. Noria Corporation reserves the right, with respect to submissions, to revise, republish and authorize its readers to use the tips and articles submitted for personal and commercial use. The opinions of those interviewed and those who write articles for this magazine are not necessarily shared by Noria Corporation. CONTENT NOTICE: The recommendations and information provided in Reliable Plant and its related information properties do not purport to address all of the safety concerns that may exist. It is the responsibility of the user to follow appropriate safety and health practices. Further, Noria does not make any representations, warranties, express or implied, regarding the accuracy, completeness or suitability of the information or recommendations provided herewith. Noria shall not be liable for any injuries, loss of profits, business, goodwill, data, inter- ruption of business, nor for incidental or consequential merchantability or fitness of purpose, or damages related to the use of information or recommendations provided. Task Volume Limitations Firstly, lubrication work involves many tasks that need to be completed daily, which can over- whelm the CMMS and lead to missed work. is can have serious consequences, such as machine failures and production downtime. Organizations can improve both programs by separating lubrica- tion from maintenance activities in the CMMS. Lacking Lubricant Information Secondly, the CMMS often lacks critical lubrication information, such as lubricant volume, type, and proper procedures. is leads to incon- sistent lubrication practices, which can impact equipment reliability. An LMS can store detailed instructions, images, and other necessary data for consistent lubrication activities. Hierarchy Constraints e hierarchy constraints of CMMS pose another challenge. Lubrication tasks often occur at the component/maintenance point level, while CMMS focuses on machine-level maintenance. is limitation prevents a detailed understanding of individual lube points and tasks. In contrast, an LMS provides a more microscopic view of equip - ment, enabling precise tracking and managing lubrication tasks at the component level. Missing Metrics for Lubrication Furthermore, lubrication-centric metrics are not adequately addressed in CMMS, hindering the ability to effectively measure and improve lubrication programs. An LMS allows organiza- tions to track lubrication tasks individually and roll up key metrics related to route compliance, contamination control, and lubricant consump- tion. is data can facilitate predictive analytics and timely lubricant ordering. Lubricated programs may fall victim to the sociopsychological phenomenon of Diffusion of Responsibility. is concept posits that an individual is less likely to take responsibility for an action (or inaction) when they are part of a group — instead of taking action, the individual assumes another group member has already done so or will do so in the future. Equipment may be over or under-lubricated without a mechanism to ensure accountability, leading to failures. An LMS can provide visibility and accountability for lubrication tasks, preventing such issues. e term Lubrication Management System exists in ICML's global standard ICML 55. is standard was written by dozens of experts in lubrication, maintenance and reliability scattered across the planet. Industry as a whole is focusing on key initiatives like reliability and sustainability. To achieve these initiatives, people are looking at standards such as ISO 55000 and, specifically for lubrication, ICML 55. ese are key standards for asset management to focus on reliability, thus ensuring the sustainable operation of a plant. Asset management may involve physical assets such as equipment, human resource assets such as people, and knowledge assets such as documenta - tion and trainings. All of these must be analyzed, and a management plan must be put in place. ere is no time like the present to get intentional with what you are doing in lubrication and reliability, and there are tools in the market to help achieve lubrication excellence. We need to stop relying on rigid CMMS structures that can't treat lubrication properly and look at an LMS that can provide the necessary information to elevate lubrication as a program, profession and pillar for world-class reliability. ML

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