Machinery Lubrication magazine published by Noria Corporation
Issue link: https://www.e-digitaleditions.com/i/847153
ML PUBLISHER Mike Ramsey - mramsey@noria.com GROUP PUBLISHER Brett O'Kelley - bokelley@noria.com EDITOR-IN-CHIEF Jason Sowards - jsowards@noria.com SENIOR EDITOR Jim Fitch - jfitch@noria.com TECHNICAL WRITERS Wes Cash - wcash@noria.com Alejandro Meza - ameza@noria.com Bennett Fitch - bfitch@noria.com Loren Green - lgreen@noria.com Michael Brown - mbrown@noria.com Garrett Bapp - gbapp@noria.com CREATIVE DIRECTOR Ryan Kiker - rkiker@noria.com GRAPHIC ARTISTS Patrick Clark - pclark@noria.com Josh Couch - jcouch@noria.com Greg Rex - grex@noria.com ADVERTISING SALES Tim Davidson - tdavidson@noria.com 800-597-5460, ext. 224 MEDIA PRODUCTION MANAGER Ally Katz - akatz@noria.com CORRESPONDENCE You may address articles, case studies, special requests and other correspondence to: Editor-in-Chief MACHINERY LUBRICATION Noria Corporation 1328 E. 43rd Court • Tulsa, Oklahoma 74105 Phone: 918-749-1400 Fax: 918-746-0925 Email address: editor@noria.com MACHINERY LUBRICATION Volume 17 - Issue 4 July-August 2017 ( USPS 021-695) is published bimonthly by Noria Corporation, 1328 E. 43rd Court, Tulsa, OK 74105-4124. Periodicals postage paid at Tulsa, OK and additional mailing offices. POSTMASTER: Send address changes and form 3579 to MACHINERY LUBRICATION, P.O. BOX 47702, Plymouth, MN 55447-0401. Canada Post International Publica - tions Mail Product (Canadian Distribution) Publications Mail Agreement #40612608. Send returns (Canada) to BleuChip Interna- tional, P.O. Box 25542, London, Ontario, N6C 6B2. 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, P.O. Box 47702, Plymouth, MN 55447. 800-869-6882 or Fax: 866-658-6156. Copyright © 2017 Noria Corporation. Noria, Machinery Lubrication 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 Machinery Lubrication and its related information properties do not purport to address all of the safety concerns that may exist. It is the respon - sibility 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 inju- ries, loss of profits, business, goodwill, data, interruption of business, nor for incidental or consequential merchantability or fitness of purpose, or damages related to the use of information or recommendations provided. Machinery Lubrication Overall Condition Monitoring Effectiveness (OCME) Team performance requires one or more metrics aligned to well-defined goals. Some metrics are micro (e.g., vibration overalls or lubricant particle counts), while others are macro to capture overall team performance. In reliability, macro metrics might look at the cost of reliability (team spending) and the overall level of reliability achieved (by condition monitoring and other activities). To illustrate the concept of a macro metric, I am introducing Overall Condition Moni- toring Effectiveness (OCME). This somewhat theoretical metric drives home several important points. OCME is defined by the overall effectiveness of condition monitoring (inspection combined with technology-based condition monitoring) in detecting root causes and early detection of failure symptoms. PROACTIVE DOMAIN PREDICTIVE DOMAIN OPERATIONAL FAILURE RUL x x x x x x x x x x 0 25 90 0 0 90 40 100 10 0 RUL 100% CONDITION MONITORING SUMMARY RC Saves = 10% Predictive Saves = 50% Misses = 40% OCME RUL 0% 35.5 INTERVAL INTENSITY Condition Monitoring Moderate Low Inspection Frequent Low CASE 1 Reportable Conditions Condition monitoring should be a team effort.