Robert Hansen C.

Overall Equipment Effectiveness


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F: Higher OEE, Selling Everything Produced, ROA

       4.The People Factor

       4.1The Most Important Resource: Actively Learning, Motivated People

      4.2Group Centering Exercise

       The Metronome Exercise

      4.3Skills, Interaction, Action

      4.4Observation and Education

      4.5Work Group Experiences

      4.6An Example of Expectations: Master Mechanics

      4.7An Example of Expectations: Technicians

      4.8Interviewing and Hiring

       4.9Ranking and Compensating

       5.Priority and Decision Tools

       5.1The Value Fulcrum

      5.2Developing a Troubleshooting Guideline Decision Tree

       6.Win-Win Maintenance/Equipment Shutdown Strategies

       6.1Steps to Improve TEEP: A Case Study

       Identify

       Exploit

       Subordinate

       Elevate

       Go back

      6.2Shutdown Strategy Checklist

       7.Reliability 101

      7.1Reliability101 Introduction

      7.2Reliability Nomenclature

      7.3Beginning Reliability with What You Have

      7.4Matching Maintenance Strategy to Equipment Function

      7.5Developing Best Practices

      7.6Building Reliability into Equipment Design

       8.Reliability Availability Maintainability/System Performance Analysis, (RAM/SPA)

      8.1RAM/SPA

      8.2Improving the ‘Horse’ you Already Have / Starting Reliability

       8.3Quick Changeovers: Single-Minute Exchange of Dies

      8.4Theory Of Constraints

      8.5Data collection and Information sharing

      8.6Pareto Analysis

      8.7Project Management and Asset Life Cycle

       8.8Speed ups

      8.9Cycle time improvements

      8.10Benchmarking

       9.A General Tool for Acceptance Testing

      9.1Reliability Quantification Testing

      9.2Implementation Stories

       Case 1. Barrel Dumper Project

       Case 2. Computer System Upgrade

       Case 3. Material Handling Wheels

       Case 4. Automatic Core Loading

       10.Success or Failure

      10.1The Success Riddle

      10.2Why Factories Fail

       Impending Failure Study

       APPENDIX

       1.Recommended Reading

       2.RAPTOR

       3.Redundancy Equations

       4.Generic Failure Rates

       5.Mechanical Failure Modes

       6.Failure Mode Effects and Criticality Analysis

       7.Constructing Pareto Charts

       8.Preserving Failure Data

       INDEX

       UNDERSTANDING THE POWER OF OVERALL EQUIPMENT EFFECTIVENESS (OEE)

      This book is the culmination of the many years of experience I have inside a large Fortune 100 company. It is offered as a “how to improve” guide for many of the issues that exist in manufacturing work centers (factories or refineries) of all sizes and types. We will look at the key parameters for the success of manufacturing communities, then link those parameters to the financial business metrics that are vital to your company’s success. We will also look at the practical application of theories that are commonly spoken, but seldom accepted on the factory shop floor.

      Aspects of this book are appropriate for everyone involved in or supporting a manufacturing process. The book provides all work centers with techniques and measures for greater throughput that requires little or no capital spending. Over the years, I have been successful in five different types of manufacturing processes. Based on that experience, I offer recommendations regarding what does and does not work to improve productivity and reliability-maintainability in both the short term and the long term. I hope you will use this book proactively to drive improvements in your area.

       1.1 Factories: Effective Producers of Good Goods

      Every factory* attempts to be an effective, low-cost producer. This effort is required in today’s challenging environment when customers demand quality product at the best value. Few factories attain and maintain high level productivity and low costs. Many of these use a disciplined approach to identify the best improvements to make. They use teams to eliminate the root problems that otherwise keep the factory from driving toward continuously higher levels of effectiveness. In short, they have found the power of OEE: Overall Equipment Effectiveness.1 By recognizing the ‘hidden factory’ within, they have made improvements that contribute directly to the bottom line.

      World-class manufacturing areas share two common characteristics. They are data driven and they are led by synergistic multi-function leadership teams. Accurately measuring and driving key success parameters contributes to higher productivity for both the area and the plant. A method called Overall Equipment Effectiveness, or OEE, can help you better understand how well a manufacturing area is performing, and identify what is limiting higher effectiveness.

      Manufacturing systems are composed of equipment and machinery that combine to transform materials and sub-assemblies into products that are either parts for the next step of manufacturing or finished goods. A significant amount of capital is often invested to design, build, and implement a system so that product can be made uniformly at a high rate with minimal waste. The factory should effectively deliver the product at less cost than would be needed to produce it individually. Every business plan should include projections about the effectiveness of the proposed system and how well it will contribute to the bottom line. The company should also be aware of the degree to which it is at risk if the expected effectiveness is not attained and sustained.

      Continuous and discrete processes of transforming materials and parts into products can be complex and unique; the system is often quite technical and elaborate. In many instances, a standard product is manufactured in many different formats and variations. The system, therefore, splinters into multiple processes, yet they use shared resources. Some of the cases in this book come from the author’s personal experience in a setting where over thirty process setups were used to produce variations of seventy different products from four different product families. The capital investment was well over $100 million. Thus, the operating cost to product was significant; the effectiveness of the operation had a major influence on the company’s bottom line.

      Nearly every industry has multiple manufacturers, each competing for its share