2nd Edition
Equipment Management in the Post-Maintenance Era Advancing in the Era of Smart Machines
Recent advancements in information systems and computer technology have led to developments in equipment and robotic technology that have permanently changed the characteristics of manufacturing equipment. Equipment Management in the Post-Maintenance Era: Advancing in the Era of Smart Machines introduces a new way of thinking to help high-tech organizations manage an increasingly complex equipment base. It also facilitates the fundamental understanding of equipment management those in traditional industries will need to prepare for the emerging microchip era in equipment.
Kern Peng shares insights gained through decades of managing equipment performance. Using a systems model to analyze equipment management, he introduces alternatives in equipment management that are currently gaining momentum in high-tech industries. The book highlights the fundamental internal flaw in maintenance organizational setup, presents new approaches to replace maintenance functional setup, and illustrates a time-tested transformation and implementation process to help transition your organization from the maintenance era to the new post-maintenance era. Fundamentally, it:
- Breaks down the history of equipment into five phases,
- Provides a clear understanding of equipment management fundamentals, and
- Introduces alternatives in equipment management beyond the mainstream principles of maintenance management.
More specifically, the book examines maintenance management logistics, including planning and budgeting; training and people development; customer services and management; vendor management; and inventory management. Supplying a comprehensive look at the history of equipment management, it analyzes current maintenance practice and details approaches that can significantly improve the effectiveness and efficiency of your equipment management well into the future.
This second edition addresses the role of the development of the Internet of Things (IoT) and significant advancements in artificial intelligence (AI) and machine learning (ML) in enabling a new generation of smart machines, which have in turn laid the foundation for Industry 4.0. Equipment utilizing IoT and sensors can monitor components and allow them to be serviced at an exact time without the need for a preventive maintenance schedule. Moreover, equipment replacement rarely occurs at the end of the piece of equipment’s natural life; rather, replacement is driven by the introduction of new technologies and products, all of which lead to less maintenance activities and reduces the importance of the traditional maintenance function. Maintenance departments today operate with fewer employees and smaller budgets. At a point when machines are smart enough to keep themselves running or equipment is rendered obsolete by better equipment in a short time, such as with computers and cellphones, companies do not need a maintenance department.
This updated edition reiterates the importance of transitioning to the post-maintenance era to effectively manage today’s sophisticated, smart yet expensive equipment. Many changes the author predicted a decade ago are accelerating in the IoT era. Equipment management is moving further away from the maintenance era and advancing deeper into the post-maintenance era. The trend for smart machines is very clear and companies that do not upgrade their equipment will lose their competitiveness. As equipment and factories become smarter, companies must change their practices and organizational structures to manage the new generation of equipment for Industry 4.0.
Contents
Preface
Chapter 1. Introduction to Equipment Management
Background
Maintenance Management
Equipment Management
Key Equipment Terminology
Chapter 2. Development of Equipment Management:
From Premaintenance to Maintenance Era
Phase 1: Breakdown Management
Phase 2: Preventive Maintenance
Phase 3: Productive Maintenance
Phase 4: Total Productive Maintenance (TPM)
Phase 5: TPM with Predictive Maintenance
Chapter 3. Advancing in the Post-maintenance Era: From Robotic Automation to Smart Machine to Smart Factory
The New Business Environment
The Issues of Maintenance
The Post-maintenance Era
Phase 6: Robotic Automation
Phase 7: Smart Machine
Phase 8: Smart Factory
Chapter 4. The Systems View of Equipment Management
Environmental Suprasystem
Goals and Values Subsystem
Structural Subsystem
Technical Subsystem
Psychosocial Subsystem
Managerial Subsystem
Chapter 5. Strategic Changes in the Post-Maintenance Era
Equipment Management Objectives
Organizational Structure Changes
The Platform Ownership Concept
Employee Skill Requirements
Work Environment Improvements
Management Changes
Chapter 6. Adoption of the Maintenance Concepts
Preventive Maintenance (PM)
Reliability Centered Maintenance (RCM)
Predictive Maintenance (PdM)
Maintenance Prevention (MP)
Total Productive Maintenance (TPM)
Terotechnology
Chapter 7. Equipment Management Logistics
Planning and Budgeting
Training and People Development
Customer Services and Management
Vendor, Supplier and Contract Management
Inventory Management
Chapter 8. Performance Indicators
Equipment Performance Indicators
Process Performance Indicators
Cost Performance Indicators
Integrated Indicators
Chapter 9. Computerized Management Systems
CMMS Functions
CMMS Features
From CMMS to CEMS
Implementation
Chapter 10. Transformation to the Post-maintenance Era
Environmental Studies
Managerial Preparedness
Initiate Goals and Values Changes
Initiate Psychosocial Changes
Initiate Technical Changes
Initiate Structural Changes
Glossary
References
Biography
Dr. Kern Peng holds two doctorate degrees, one in mechanical engineering specializing in nanocomposite materials, and the other in business administration specializing in operations management. He also holds an MBA in computer information systems and a BS in industrial engineering.
Dr. Peng designed and has been teaching the Equipment Management course at Santa Clara University, Santa Clara, California, since 2001. In addition, he regularly teaches four other master level courses in engineering management at SCU. Before that, he also taught MIS courses at San Jose State University, San Jose, California.
Dr. Peng has more than 26 years of people and project management experience in engineering and manufacturing, with over 19 years at Intel Corporation. He has mastered all aspects of engineering and manufacturing management and has proven results in finding innovative solutions to business and engineering problems. He has been accorded more than 50 career awards in the areas of engineering design; software development; technical paper publication; problem resolution; project management and execution; teamwork; and leadership.