Basim Al-Najjar, CeIAM

Centre for Cost-effective Industrial Asset Management

Centre for Cost-effective Industrial Asset Management is a research group that does research within the field of cost-efficient maintenance techniques.

Our research and CeIAM

Due to the hard competition on the international market, companies strive to assure, maintain and improve the achievements in the following competitive advantages in order to secure and enhance their market shares:

  1. High quality production and assets
  2. Competitive price
  3. Delivery on time
  4. Environmental friendly production process and product
  5. Society acceptance

Strategies for cost-effective and dynamic maintenance decisions that contribute in company competitiveness are necessary to be considered in order to enhance maintenance decisions continuously. CeIAM provides tools, methods, and technical and economic criteria required to select the most cost-effective maintenance techniques and the most informative condition monitoring (CM) parameter.

In CeIAM, maintenance aims to maintain the quality of all involved in a production process cost-effectively. Also, the role of maintenance in CeIAM is for monitoring and controlling deviations in the condition of a process, working conditions, human resources, product quality and production cost. Also, for detecting damage causes and their developing mechanisms and potential failures in order to interfere (when it is possible) to "stop" or reduce component/machine/process deterioration rate before the production process and product characteristics are intolerably affected and to perform the required action to restore the machine/process to as good as new. All these should be performed at a continuously reducing cost per unit of good quality product.

Four essential working phases

These competitive advantages can be achieved, maintained and improved by using the concept of Cost-effective industrial asset management (CeIAM). It consists of four essential working phases (modules). Theories, tools and methods are specially developed or adapted for the application of the modules which are verified in several case studies. The modules are for:

1) Identification: Identification of critical/strategic assets & significant components

  • Failure and condition-based replacement data, and operational data
  • Risk analysis & management, and statistical modelling
  • LCC and maintenance related economic factors
  • Significant machines, sub-systems and components

2) Description: Description of the changes in component/equipment status and relations

  • Changes in the condition of the component
  • Changes in the product technical specifications
  • Relations man-machine-maintenance-economy

3) Selection: Selection of the relevant theories, tools, methods, criteria & measures

  • Selection of technical, managerial and economic criteria and performance measures
  • Selection of the most informative/ cost-effective CM parameter/system
  • Selection of the most cost-effective maintenance strategy and policy
  • Selection of the basis for integrating maintenance and plant disciplines for identifying and quantifying the economic losses in order to eliminate the root-causes cost-effectively

4) Cost-effective application and cost-effective & continuous improvement

  • Integration of maintenance with the other disciplines in the plant
  • Cost-effective implementation
  • Identification of the information parameters for production process monitoring
  • Development of measures for following up performance & benchmarking
  • Data acquisition and management, databases and information systems
  • Strategies for cost-effectiveness Continuous and cost-effective improvements

Machine failure

In general, companies lose profits due to discontinuity of the production because of machine stoppage due to failures (or disturbance). Machine failures occur due to the failure of a significant component whose failure is either expensive or dangerous. When the critical (strategic) assets have been identified in the first phase, the major focus would be to collect relevant data for mapping and analysis the situation to identify; significant components in the critical assets, their failures, damage initiation causes and the mechanisms for developing the damage. The output of this phase is utilised to describe the possible changes in the state of the component/equipment under consideration when the damage is initiated and is underdevelopment until failure. In other words, the changes in the state of the component and in the relations between the element involved in the production process, such as man, machine, maintenance and economy, can then be described properly.

When the latter is done, the most informative CM parameter(s) and consequently systems for detecting changes in equipment condition, working environment, production cost, maintenance performance, etc., and follow up their development can be identified effectively. CM systems are to detect deviations in the quality of the elements involved in the production process and only machinery at an early stage. CM technology is one of the information sources that can be utilised for mapping and analysing the condition of a component, equipment and process. But, the management work required for planning and performing relevant and cost-effective maintenance actions necessary for maintaining the quality of one or more of the elements involved in the production process is very important. Also, it is essential to cover wider range than CM technology to include man, organisation and working environment on the economic bases for developing as big as possible part of the holistic view of the production process.

Characteristics of CeIAM

The features characterising CeIAM can be summarised in the following:

  1. It covers a wide range of a production process and not just machinery.
  2. It is based on a new CBM concept. It is planned and performed based on the needs arise due to the deviations in the quality of the elements involved in the production process.
  3. It handles production, quality, working environment, competence and maintenance technical and economic problems by integrating tools and methods belong to both deterministic and probabilistic approaches.
  4. It advocates the use of a common database that should be updated by real-time data of the essential information parameters for; real-time monitoring and assessment of the machine condition and production process technical and economic effectiveness, product quality and working environment. It is possible to select and improve the most informative CM system and the most cost-effective maintenance policy effectively by applying CeIAM.
  5. Consequently, it provides an overall view of the state of the production process (including all the elements involved), and maintenance technical & economic impact on company's business
  6. It is based on making intensive use of the real-time data acquisition and analysis to detect at an early stage the causes behind quality and cost factors deviations and machinery malfunctions, and following damage/defect development to prolong the component and consequently machine mean life.
  7. It provides tools and methods for proactive-predictive maintenance, i.e. to detect and eliminate the cause behind damage initiation. If it is not possible technologically, detect the deviation at an early stage and predict its development to reduce (or eliminate) the risk of failure.
  8. It emphasis on the systematic maintenance work combining technical, organisational and economic knowledge and experience, where all the theories, tools and methods required are developed and verified.
  9. It provides the basis for cost-effective & continuous improvement of the whole production process and in particular vibration/CBM policy after each renewal through confronting history, (vibration measurements) with the replaced components, i.e. continuous cyclic improvement. Cost-effective improvement means that every improvement should be judged in conjunction with its cost-effectiveness and not just how technically advanced it is.
  10. CeEAM has been applied partly in about ten case studies. The results of these applications have shown a big beneficial potential.

Benefits and applicability of CeIAM

The effective use of data is considered essential to accomplish cost-effective & continuous improvements and to assure the achievement of the competitive advantages demanded. It would enable the user, on demand and at all levels, to:

  1. Map production and maintenance processes technical and economic situation.
  2. Follow up their performance development.
  3. Benchmark the process with itself or other process.
  4. Identification of technical, economic, environmental & organisational problem areas, problems and root-causes at an early stage for enhancing company profitability and competitiveness.
  5. Simulate relevant solutions for selecting the most cost-effective.
  6. Cost-effective and dynamic decisions for maintaining the quality of the elements involved in the production process.

All these benefits can be achieved through acquiring reliable information gathered and managed by CeIAM that can be utilised for:

  1. Detecting the deviations in the state of a component, machine or process.
  2. Selecting the most cost-effective maintenance policy and the most cost-effective condition monitoring level, such as vibration level, at which to replace components.
  3. Selecting the acceptable deterioration rate to "guarantee" no sudden failure during the lead-time, i.e. the time between detecting a potential failure and action to repair it.
  4. Detecting potential failures (damage under development) in machine element and follow up their development, and predicting the level of the condition monitoring parameter, such vibration level, during the close future.
  5. Assessing the condition-dependent failure rate of the component during the lead-time, the probability of failure, the remaining useful working lives (residual life) of the components/equipment under consideration, and the most cost effective opportunity for performing maintenance action.
  6. Identification of failure mechanisms, failure causes and failure modes with increasing diagnosis and prognosis precision by relating the past measurements to the damage subsequently found and safe lead-time achieved.