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Editorial November 2011
Volume 7, Number 6, November 2011
KRISHNA B. MISRA
In asset intensive industries, such as automotive (railways, airlines, ships, road transport etc), metallurgical, mining, oil and gas, process manufacturing, general utilities, etc., the performance of assets is crucial for the financial success of the industry. Maintenance of these assets can drastically impact the overall performance and useful life of the assets. According to an estimate, that by using predictive maintenance practices, system can save up to one-third of the total maintenance costs, which in the US alone would amount a saving of about 60 billion US-dollars per year. Therefore the asset owners, operators or asset service providers continuously strive to refine and improve the effectiveness of maintenance operations.
The field of maintenance changed dramatically after the World War II. By 1950's, systems had became more complex and large, and the concern for the uptime of these systems became the priority of the industry and the management. This became the rallying point for the concept of preventive maintenance with the realization that performing regular maintenance and refurbishment could keep equipment operating longer between failures. This came to be known as Periodic Maintenance, or Calendar Based Maintenance or Preventive Maintenance (PM) or planned preventive Maintenance (PPM). The goal was to have most of the equipment be able to operate most of the time until the next scheduled maintenance outage. This approach provided control over the maintenance schedule; however, the systems were still susceptible to failures between maintenance cycles. Opportunistic Maintenance is an extension of planned maintenance and is actually planning of maintenance around opportunity for access to equipment.
Even by 1960's, the concern was mainly confined to the overhauls of equipment done at fixed intervals. But as the cost of maintenance increased the necessity of maintenance planning and control systems was felt. In fact, the amount of capital tied up in fixed assets increased enormously and the necessity of maximizing the life of these assets was felt more acutely.
As the downtime reduced output, it affected the productive capability of physical assets by increasing operating costs and interfering with customer service and by 1970's, this was further aggravated by the worldwide move towards just-in-time systems, where reduced stocks of work-in-progress meant that quite small breakdowns could stop the whole plant. Instead of waiting for a machine to fail before working on it, or performing maintenance on a machine regardless of its condition (PM), the idea of performing maintenance on equipment only when it indicates impending faults – Predictive Maintenance (PdM) – took hold and the idea of using PdM to perform maintenance on machines only when they exhibit signs of mechanical failure had come to be known as Condition Based Maintenance (CBM). This process of maintenance has become more proactive than reactive in their maintenance tasking. Moreover, the cost of maintenance is also rising, in absolute terms and as a proportion of total expenditure. In some industries, it is the highest or the second highest element of operating costs. Consequently, in last thirty years it has moved from almost nowhere to the top of the cost control priority. Also it is becoming apparent that there is less and less connection between the operating age of the assets and how likely they are to fail.
In recent times, there has been tremendous growth in the maintenance concepts and techniques. The change in emphasis includes:
It is now possible to improve asset performance and at the same time contain and even reduce the cost of maintenance by choosing the right choices of techniques.
Reliability Centred Maintenance (RCM) provides a framework which enables users to respond to these challenges, quickly and easily. RCM uses failure mode and effect analysis (FMEA) in order to identify significant components and failure modes. This helps in selecting the appropriate maintenance action for preventing such future failures.
Total Productive Maintenance (TPM) and Total Quality Maintenance (TQM) are the means to maintain and continuously improve the technical and economical effectiveness of production process. The TPM optimizes the effectiveness of production means in a structured manner.
Maintenance Information and Control Systems started with charts and indexes. For large assets, the computerized models were developed for managing and controlling large inventories. Early computerized systems tended to concentrate on job scheduling, resource management and inventories. But CBM has now developed more sophisticated tools such as vibration analysis etc. The standardization of maintenance data was significantly advanced by MIMOSA (Machinery Information Management Open System Alliance) which is ISO 13374-1 compliant. Computer-based systems starting from the perspective of enterprise resource planning started coming in vogue.
Computerized Maintenance Management System (CMMS), which is also known as Enterprise Asset Management (EAM) is a stand alone computer program to schedule and manage the entire maintenance related activities.
Fast and reliable internet and mobile networks have opened up boundless opportunities for system information integration. CBM uses a wide range of devices and equipment to monitor the health of the machines and processes. For predictive maintenance (PdM), which helps determine the condition of in-service equipment in order to predict when maintenance should be performed, any relevant means is acceptable to determine equipment condition, and to predict potential failure, which may even include the use of the human senses (appearance, sound, feel, smell etc.), machine performance monitoring, and statistical process control techniques. But the other sophisticated technologies used in monitoring include:
The major trends today are:
Today, wireless sensors, MEMS, with reduction size and power requirement the devices, have further revolutionized the system of monitoring and recording and analyzing of maintenance data. Miniaturization of transducers for the measurement of pressure, strain, acceleration, angular displacement, force, flow temperature etc. has revolutionized the practice. Better and better diagnostic, monitoring, signal analysis and prognostics approaches are available. Expert systems have been developed for carrying out maintenance related activities and decisions. The area of PHM (Prognostics and Health Management) is assuming importance and is becoming indispensable. We had a special issue exclusively devoted to PHM in this journal’s (IJPE) September 2010 issue. All this is making the task of e-Maintenance feasible and real. In the present issue we explore the current thinking in the area of maintenance leading to e-maintenance. It is hoped the readers would find the papers included in the current issue rewarding in familiarizing and exhorting to further research.
Of recent, emphasis is being placed on core business by several major companies of the world and under this thinking; companies are transferring previously in-house functions to external specialist companies. Use of experts or specialists and reasons for choosing in-house teams on-site accommodated teams or manned-up technicians brought from outside for the completion of a job, is becoming routinely common these days. Subcontracting for maintenance job is also becoming quite common in the globalizing world of trade these days and the number and size of companies engaged in maintenance work is growing very fast.
I take the opportunity to thank the Guest Editors and reviewers, who helped bringing out this issue and lastly thanks are due to the authors who contributed to this special issue and cooperated in maintaining timeliness and standards of presentations.