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Abstract
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Management summary
While many organizations are focused on Maintenance cost reduction, process improvement and outsourcing of responsibilities to contractors, this empirical research conducted in the Dutch resources industries reveals that companies that invest in Maintenance and that improve their predictive asset maintenance skills are able to turn around the cost cutting trend and enhance overall business performance.
The research report features insights from maintenance-, asset-, and plant managers in 32 companies located in The Netherlands across three industries namely, Chemicals, Energy and Utilities. The research is conducted by means of the interview technique and addresses maintenance departments’ performance, capabilities, maintenance strategy, drivers and enablers for predictive asset maintenance. All in all, this has resulted in determining the maintenance maturity and defining the success factors of predictive asset maintenance.
Respondents of the research perceive their maintenance performance as high. In fact,
• 94 percent consider themselves top-half performer on availability;
• 84 percent consider themselves top-half performer on SHE-incidents;
• 57 percent consider themselves top-half performer on maintenance cost as % of asset replacement value.
The general remark is that there is high potential to improve on all three performance indicators.
In order to assess how mature maintenance departments are, a capability staircase has been developed. This staircase consists of nine capabilities and is seen as an applicable model within the context of the research. It is concluded that maintenance departments operating in the Dutch resources industry are on their way to PAM. More precisely, 78 percent is not able to predict maintenance, however 100 percent is trying to, since all tested companies applied condition monitoring. Only 22 percent is already capable of predictive asset maintenance.
Respondents are motivated to change the current situation and want to improve their maturity. The assessment of the degree in which corrective - preventive- and predictive asset maintenance strategies are applied show the gap between the current and desired situation. Overall, most urgent is the simultaneous increase of predictive asset maintenance and decrease of corrective maintenance. This conclusion also holds in the context of the energy and chemicals industries. Within utilities however, the market conjuncture and subsequent developments have resulted in an insecure market. Utilities companies therefore have relatively low ambition to develop their maintenance department. This is reflected in the distribution of the current and ambition maintenance strategies. The ambition is a slight increase in predictive asset maintenance and slight decrease in corrective maintenance.
That companies do want to improve becomes clear once again. It is believed that the application of predictive asset maintenance on the long term will cause:
• an increase in availability due to preventing from breakdowns;
• a decrease of SHE incidents due to mitigated risk and preventing from breakdowns;
page | 4 Maintenance departments within the Dutch resources industries are ready to change the organization. The incentive for respondents to change is provided in the research by a ranking of drivers. Overall, SHE-incidents, process reliability and maintenance cost are seen as the most important drivers.
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Table of contents
Abstract ... 2 Management summary ... 3 Table of contents ... 5 chapter 1 | introduction ... 7 1.1 | research context ... 7 1.2 | functional problem ... 8 1.3 | research objective... 8 1.4 | research questions ... 9 1.5 | deliverables ... 9 1.6 | research boundaries ... 10 1.7 | research approach ... 10 1.8 | report outline ... 11chapter 2 | literature research ... 12
2.1 | the context ... 12
2.2 | the maintenance landscape ... 13
2.3 | maintenance trends in resources industries ... 16
2.4 | theories to improve ... 21
2.5 | maintenance performance ... 22
2.6 | maintenance strategies ... 28
2.7 | maintenance capabilities ... 32
2.8 | enablers of predictive maintenance ... 34
chapter 3 | research design... 36
3.1 | research outline ... 36
3.2 | research model ... 37
3.3 | research method ... 42
chapter 4 | maintenance performance ... 47
4.1 | availability ... 47
4.2 | maintenance cost as % of ARV... 50
4.3 | SHE incidents ... 52
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chapter 5 | maturity of maintenance ... 57
5.1 | maintenance maturity ... 57
5.2 | conclusion and discussion ... 60
chapter 6 | maintenance strategies and drivers ... 62
6.1 | maintenance strategies ... 62
6.2 | drivers ... 65
6.3 | conclusions and discussion ... 67
chapter 7 | enablers for PAM ... 69
7.1 | research results - enablers ... 69
7.2 | research results - obstacles ... 73
7.3 | conclusion and discussion ... 75
chapter 8 | conclusion and recommendations ... 78
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chapter 1 | introduction
1.1 | research context
Performing maintenance is part of the daily business in production companies. The use of replacement parts and commitment of employees in order to fix a breakdown is relentless. Maintenance is traditionally seen as a cost center since the activities add to the costs companies make. In the last decennia competitiveness in the industry increased due to globalization and external influences. A lean and decisive operation becomes more and more important. Srivastava (2004) stated that companies should use more effective and efficient strategies to operate successfully by increasing violent competition. And, of equal importance, there is stressed that in fact optimizing maintenance can contribute to a more effective and efficient operation.
Scope.
The entities for which optimization of maintenance is relevant are the industries who work with leading products, precious assets and bear high responsibility for safety and environment. The three Resources Industries that match this profile are Energy, Chemicals and Utilities (figure 1). For companies within these industries it is necessary to invest in maintenance to stay successful in the future. Another characteristic is that the operations department is highly dependent on maintenance performance.
Figure 1: Subdivision of the scope in three asset intensive industries Chemicals – Energy – Utilities
With the Energy industry is meant the oil and gas companies. This can be distinguished in ‘upstream’, ‘midstream’ and ‘downstream’. Upstream is involved in exploring and producing oil and gas from below the surface. Midstream contains the gathering, storage and distribution of the raw product to a refinery or chemical plant. The downstream business concentrates on refining the raw product in consumer products. And, if the raw product is processed by refineries or chemical plants, the (semi) finished products are transported to the client or end-user. Also within scope is the manufacturing of chemical products by the Chemical industry. The business uses chemical reaction to turn raw materials, such as oil, salt and coal into a variety of products. Furthermore, a distinction can be made in the production of ‘gases’, ‘liquids’ or ‘solids’. To differentiate between Utilities companies a convenient split can be made between ‘generation’ on the one hand and ‘distribution’ on the other hand. Generation is about the production of typical utilities like water, energy and gas. The distribution comes down to the delivery of end products to business and end users.
page | 8 characteristics have its influences on the maintenance organization. A long term vision and continuity in maintenance operations are required to add value to the business.
Relevance.
A market research of the NVDO shows the Dutch asset base represents a total value of 225 billion euro in 2007. The maintenance these assets require can be traced by looking at the employment; in 2007 the maintenance market employs 300.000 people in The Netherlands, compared to 260.000 people in 2012. This equals about 4% of the working population active in the maintenance sector. Future expectations of further developments are unknown.
Stakeholders.
As a part of this Thesis, empirical information is gathered by a research. The University of Groningen is a stakeholder by supervising the process and assessing the Thesis. A scientific contribution is made by collecting and analyzing the empirical data. Accenture has a facilitating role by supporting the research and providing knowledge and resources in order to execute the research. Empirical information out of the research increases the level of knowledge on this subject, the Accenture employees are eager to learn from this. An important prerequisite for the research is the collaboration of companies to deliver input. Participating companies benefit by starting the discussion about the future of maintenance and are invited to learn from each other by joining the conversation.
1.2 | functional problem
Accenture wants to provide management consulting on the highest level to their clients in the Resources industries now and in the future. To be able to keep the leading position in this market and in the area of maintenance it is necessary to keep the knowledge at the appropriate level. Accenture has to be aware of developments in the field. A study on the current maintenance situation and on Predictive Asset Maintenance (from now on PAM) will facilitate all interested parties.
1.3 | research objective
The aim of the research is fourfold. • As a first objective the current maintenance performance will be mapped by investigating the Dutch Resources Industries. • Also as a part of mapping the current status the maintenance maturity of the Dutch Resources Industries will be determined. • Subsequently there is aimed to identify the gaps between the future state and the desired future position, as well as the key incentives to change the current situation. • To conclude, an open discussion with industry specialists about PAM, will define the success factors of PAM.
page | 9 The added value from this thesis is an increase and update of the knowledge about the maintenance practices. To be more specific, a benchmark on the maintenance performance within the selected industries is provided in a qualitative way, as well as a benchmark on the maintenance maturity. The empirical study shows the most important business drivers for the development of maintenance. The identification of blockers and enablers of PAM together form a best practice. The value of introducing industry specialists as well as maintenance professionals to develop the vision on PAM will add to scientific knowledge since there is little understanding in scientific literature about how to implement PAM and become successful. Regarding stakeholders this knowledge can be used for internal learning and provision of improved management consulting services. An external gain can be found in the distribution of the scientific knowledge by means of publication of the benchmark findings, empirical data and best practices.
1.4 | research questions
On high level the objective of this research is translated into the following main question: How mature is maintenance within the Resources Industries and
what are the success factors of Predictive Asset Maintenance?
In order to realize the research objective, sub questions need to be answered which support the main question. The key sub questions are listed below:
1. How do maintenance organizations currently perform?
2. Which maintenance strategies are currently applied in the Resources industries?
3. How is maturity of maintenance determined, and how mature are maintenance organizations?
4. How will the application of PAM develop in the coming years?
5. What are the underlying reasons for the decision whether or not to apply PAM?
6. What are any restrictions and or accelerators for application of PAM?
7. What can be considered leading best practice?
8. What are opportunities for benchmarking?
1.5 | deliverables
i. The literature research, empirical research and results are described in this thesis and delivered to University of Groningen as well as Accenture. This report is intended for internal use and is the main deliverable. The goal of the thesis is described in paragraph 1.3 research objective.
ii. Organization of a round table for companies that participated to the research as well as other related companies. The purpose of such a round table is to update third parties about the current state of maintenance and create awareness for the value pockets of PAM.
page | 10 iv. As a final deliverable, based on the theoretical and empirical research, input will be delivered for a Point of View. Primary it is intended to inform third parties about the maintenance status and success factors of PAM, in such a way that it will enable knowledge distribution.
1.6 | research boundaries
The research will focus on maintenance of assets. Assets are tangible units that require maintenance and contribute directly or indirectly to the core manufacturing processes of an organization. Maintenance on buildings, for instance, is therefore out of scope. The reason for this is that the approach of maintenance for this kind of business differs substantially.
The research related to PAM focuses on the design, development and implementation of the concept on a managerial level. The business effects of the application of PAM (e.g. possible effects on number of breakdowns, maintenance cost, operations, inventory, ROI) are situation dependent and are outside the boundaries of this research.
1.7 | research approach
After four sequential steps the research is concluded by a thesis. In figure 2 the research approach is shown in a model is drawn to provide a high level overview of the actions taken in time.
Figure 2: Model for the research approach. And, a draft of the research model.
page | 11 maintenance strategies are defined • what drivers possibly are of importance • and what typically enables PAM. On that literature basis a research design is drawn up, the research elements are included in the research model and is filled out and further explained in paragraph 3.2 and 3.3. In order to gather high quality data and be successful in the approach of respondents for the empirical research it is of importance to be properly prepared. The third step concerns the gathering of empirical data at selected companies that operate within the scope. Based on the research questions a logical framework is designed that covers all aspects of the research questions. The framework in combination with structured interview questions ensures creation of the necessary content for the analysis later on. After applying the interviews, the maintenance situation within every participating company is assessed. Ranking of performance metrics by individual respondent leads to a performance benchmark. Further on, the analysis shows what criteria regarding maturity are met by each company. To conclude the analysis empirical data give insight in success factors of PAM. The remainder has to do with visualization of the results, describing the analysis and drawing the conclusions.
1.8 | report outline
This report will continue with a discussion of the literature that is used as a fundament for the research. • Chapter 2 is written based on relevant academic work in the field of maintenance, operational performance and asset management. Important concepts which are used throughout this report are explained. The theories that play a part in the research are introduced as well in the literature chapter. This is done since literature is also used to build the research model. • To continue, the research design will be further explained in chapter 3. Provided knowledge in the previous chapter is of critical importance in order to be able to build the research model. This is a framework that functions as a basis for the interview and therefore for the interview questions. A structured method ensures collection of the right data which is processed in the four following chapters. This is in accordance with the approach already shown in figure 2.
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chapter 2 | literature research
Review of relevant literature has led to insights which are elaborated on in this second chapter, kicking off by describing the context of the subject. Cohesion with related business processes shows the relevance of maintenance. This is explained by taking a view on the maintenance landscape. By reviewing the landscape of maintenance it is important to make the connection to Asset Management. Subsequently, the impact and the maintenance process are explained.
After that, trends are described, and to adhere to the scope, specific trends in resources industries will be elaborated upon. Important general and specialist terms are clarified in this chapter to help building the context. Then applicable literature is cited to build the empirical study upon, for instance maintenance performance, capabilities, and enablers of PAM.
2.1 | the context
A broad view in literature on the topic of maintenance shows the diversity on how this conception is regarded. Within every industry it seems to play a fundamental role. When it comes down to buildings and construction or roads and highways, after the design and construction it is essential to develop an appropriate maintenance program in order to optimize the total lifetime (Sanchez-Silva M., 2008). In the area of transportation the paper of Vujanovic (2012) shows that maintenance can realize cost reductions to fleet management. Fleet management plays a role in the aircraft, ship and road transport industries. In terms of maintenance the focus lies on safety, whereas the main goal in the process industry is delivering continuity of production output. In many cases the process industry makes use of highly specialized and durable assets to enable a high rate in production of consumables. In this field, Parida (2007) argues that the main goal of maintenance is to ensure reduction of risk to a minimum and meanwhile increase uptime of assets.
To conclude, it stands out that maintenance plays a crucial role whenever substantial investment is done in hardware. Either extended lifetime or proper return on investment drive the technical and economic value of maintenance. A new and upcoming area of interest is ‘software maintenance’. Just as on tangibles this new field in maintenance is of crucial importance. Since a few years this topic is described in detail in scientific literature. Xiong (2011) already describes that end users of software rely more and more on the availability of software services. A very interesting area, since software maintenance is one of the main reasons that make software unavailable and is often very expensive to perform. With respect to the future of maintenance, this could also be a topic of interest. However, for now, the focus in the rest of this report is on traditional maintenance.
page | 13 Figure 3: Most important assets for asset management in the process industry (De Leeuw, 2007)
In many cases the investment in such assets is high. Next to manpower, assets are what the company needs to manage. When aiming for maximum profit, it is important the assets function properly. Constant performance of assets is important when a quick return on investment is desired. Maintenance plays a fundamental role in these objectives.1
2.2 | the maintenance landscape
In the ‘Glossary of maintenance management terms in terotechnology’ of 1984 the term maintenance is defined as the combination of all technical and administrative actions intended to retain an item in, or restore it to, a state in which it can perform its required function. This is similar to the explanation of Geraerds (1992); the total of activities serving the purpose of retaining the production units in or restoring them to the state considered necessary for fulfillment of their production function.
In that sense maintenance also takes into account the replacement of parts that are broken or will in the near future. Other examples of basic maintenance tasks are lubrication and adjustment of components. The slightest intervention of maintenance can cause a shutdown of an entire production process. Therefore, maintenance is often seen as a cost center. Haarman and Delahay (2003) mention this in their book and substantiate this with arguments. According to them, an important reason is the inability of the maintenance manager ‘to speak the management language’. Maintenance managers do not speak in terms of economic added value or shareholder value. Their responsibility can be seen as a cause. A maintenance manager is often faced with safety issues and risk reduction, where a manufacturing manager navigates primarily on the economic indicators. Meanwhile, both are responsible for asset management and therefore have a shared interest.
Link with asset management.
To be more clear about the work area or landscape of the maintenance manager it is important to point out their role to the economic aspects. Maintenance is an activity associated with availability of assets. Just like other business domains such as scheduling, production and engineering, the maintenance department is trying to optimize asset performance. The common key indicators have
page | 14 to do with the effectiveness of the equipment and their productivity. Although, maintenance is often seen from a cost perspective rather than as a source of profit, it can function as an accelerator for high performing assets. If maintenance focuses on lengthening the effective life of assets while production keeps going, the cost of capital lowers by improving returns on existing capital goods. In such a way, unnecessary assets are eliminated and capital investment can be delayed. These financial mechanisms help to increase the added value of assets in the supply chain. Asset management is supported by maintenance, as such it enhances the company’s profit (De Leeuw, 2007). According to Wenzler (2005) asset management is a process of identification, design, construction, operation and maintenance of physical assets. Mitchell and Carlson (2001) see it as a strategic, integrated set of comprehensive processes to gain greatest lifetime effectiveness, utilization and return from physical assets. An interpretation of their asset management framework is shown in figure 4. According to Moubray (1992) maintenance plays an important role in assuring the integrity of assets and thereby in assuring the reliability, safety and sustainability of capital assets.
Figure 4: An interpretation of the asset management framework
Another bond between asset management and maintenance is the responsibility for optimization of the life cycle of assets. Apart from high utilization – which of course also depends on manufacturing, demand or scheduling – the cost needs to be minimized and useful life brought to an economical optimum. Applying the right maintenance in this context requires a long term vision. Meanwhile, extending the useful life of an asset optimally is a mandate for insight in future expected maintenance, also known as predictive maintenance (or in this context predictive asset maintenance; PAM). (De Leeuw, 2007)
Considering these different authors, it can be concluded that asset management can be seen as a systematic process of operating, maintaining, upgrading, and disposing assets cost-effectively. Predictive asset maintenance is directly linked to the performance of assets and, therefore, to asset management. Maintenance is a factor that requires attention from the beginning to the end of an asset’s lifetime. The origin of predictive asset maintenance management lies in the basis of asset management, since technical- as well as economical lifetime are determined by those concepts.
Impact of maintenance.
page | 15 up between 15 and 60 percent of total operating cost, dependent on the specific industry. In food related industries, average maintenance costs represented about 15 percent of total operation cost. Whereas in heavy industries (e.g. iron and steel, pulp and paper) maintenance can represent 60 percent, due to extreme wear. However, there is mentioned that percentages may be misleading since reported maintenance cost sometimes include many non-maintenance-related expenditures (e.g. modifications to existing processes). To continue with Zhao (2010) who specified maintenance cost as percentage of total operational costs for different industries;
•••• manufacturing companies 15%
•••• chemical industries 20-30%
•••• iron and steel industries 40%
Overall, it is justified to state that the importance of maintenance increases. Therefore, a continuous search for better maintenance policies is legitimate since it provides economic efficiency with higher system availability, reliability and safety. These transformations are reflected in the strategy that maintenance departments apply; a switch from reactive maintenance towards more proactive maintenance. The range and differences in maintenance cost for the particular industries that are shown by the authors probably tells something about ongoing trends in the maintenance landscape, which are further discussed in paragraph 2.3.
The maintenance process.
Literature is not unequivocal about that what belongs to the maintenance process. Hassanain (2003) explored the field of maintenance, he concluded that the increasing professionalization of asset management has led to development in areas such as project management. However, the level of knowledge within maintenance departments appears to be less developed. This also holds for the development of maintenance strategies – the different maintenance concepts – and application of maintenance techniques. Both in practice and in literature defining the maintenance process appears to be a difficult challenge.
The maintenance process has been described generally by Parida (2007), starting with the maintenance objectives and strategy, which are in line with the corporate vision, goal and objectives. A maintenance program is developed based on the maintenance objectives, policy or underlying strategy, organizational implications, resources and capabilities. The program is broken down into different types of maintenance tasks. For example this could be repair, replacement, adjustment, lubrication, modification or inspection of assets. It is important that management understands the importance and acknowledges the role of maintenance within the organization. A plan to realize the vision, goal and objectives of the organization can then be matched to the context of the maintenance department.
page | 16 Figure 5: Decision making and actions on different hierarchical levels translated to maintenance
According to Hopp and Spearman the hierarchy is divided into three basic levels, corresponding to long-term (strategy), intermediate-term (tactics), and short-term (control) decisions. To adhere to the focus of this thesis, strategy in this sense means ‘plant strategy’.
The basic function of making long-term strategic decisions on various issues related to maintenance management is to establish an environment capable of meeting the plant’s overall goals. To assure the maintenance process functions as it is intended, decisions have to be made at plant level. Some are drawn up in figure 5 and explained here. From a strategical viewpoint it is prudent to match the operational capacity with demand. In order to maximize utilization availability goals have to be set, which are input for maintenance management. Another example to strategically focus maintenance on the right assets or materials is performing a risk analysis. Indicating risks contributes towards safety and performance, besides, it opens up opportunities for more intelligent forms of maintenance. When it comes to tactics more ‘active’ cases have to be solved. Supporting an effective and efficient maintenance operation requires sufficiently skilled maintenance workers and spare parts at the right time in the right quantity. Monitoring strategically chosen indicators will activate mid-term control and expose the need for improvement of the maintenance process. Based on short-term decisions, maintenance is executed on the systems with the highest priority. Also other indicators like vibration of parts are typical short-term control activities.
The benefit of these hierarchical levels lies in the opportunity to discriminate between decision-making problems on different levels. The hierarchical levels help in applying maintenance management effectively.
2.3 | maintenance trends in resources industries
In recent literature tendencies related to maintenance are identified and summarized. To be more specific these trends are being found in literature about, and closely related to, resources industries.
Call for asset management.
page | 17 2007). This trend demonstrates the increasing focus on operational and maintenance cost. The key challenges for maintenance managers according to De Leeuw are:
•••• Monitoring and prediction of asset health;
•••• Improving performance of existing assets;
•••• Improving Total Cost of Ownership
There is a need to establish integration of corporate processes such as maintenance with asset management. Investigation also showed that the technical requirements for proper asset management are well established (e.g. IT systems for asset control, monitoring equipment for data collection etc.). Methods, standards and integration between maintenance and asset management still need to be improved. This indicates the lack of process design on a managerial level.(De Leeuw, 2007)
Lifetime extension.
A recent study of Pérez (2013) gave insight in the problems the oil and gas industries encounter. Oil companies invested heavily in the 50’s and 60’s of the previous century. The dependence of consumers and the business on widely accessible fuel, gas, water and electricity is tremendous. Construction of subterranean and over ground resources has increased ever since. While assets deteriorate over time the maintenance department is running lifetime extension programs with the purpose of maximizing return on investment. The urge for effective measures in order to extend the life of installations that are approaching, or have passed the end of their design lifetime becomes clear in the study of Pérez. The same concept can be put in a wider context since it also applies to utilities and other asset intensive industries.
To adhere to the scope, maintenance-trends within the Dutch industries are presented. The NVDO published the trends in the ‘Onderhoudskompas’ (2012). A survey was conducted to identify the trends in the Netherlands under more than 130 maintenance-related people. Six sectors of interest are part of the scope, which are; Infra − Fleet − Manufacturing − Process industry − Food, Beverage & Pharma − and Real Estate. The five most important trends are being discussed hereafter, the following trends are increasing:
•••• Scarcity of technical workers;
•••• Need for subcontractors;
•••• Dependence on technology and knowledge;
•••• Tightening of regulation and need for compliance;
•••• Influence of shareholders and investors. Scarcity of technical workers.
page | 18 statistics) reported a decrease in intermediate vocational education (‘MBO’) from 156 thousand students in 2012 to 139 thousand in 2013. The highest demand in Dutch industries lies in technical knowledge; 30 % of the responding companies state their desire, as shown in figure 6.
Figure 6: NVDO Survey shows the distribution of required knowledge in Dutch industries
Need for subcontractors.
Subcontractors are usually specialists who are hired to do a job for another company. Making use of this kind of outsourcing differs from sector to sector. The NVDO reports that the Dutch industry outsources on average 55% of its maintenance activities. It is expected this number will grow over time. Maintenance is in the top five of outsourced activities. In the short term this will lead to more specialization in the sector, since specialists are required to do the job. Besides, another trend shows the increasing need for certification; an opportunity for experts in the field. In the long term the outsourcing of more maintenance tasks will bring along the drainage of internal knowledge.
Dependence on technology and knowledge.
The technical systems and matching knowledge of today are outdated tomorrow. The survey provides insight into the burning developments of the interconnection of technical systems. In fact, this means more and more assets, people etc. are dependent on data that need to be connected to the internal IT systems. Automation has a huge impact on the maintenance organization, as well as on the maintenance job. Since it becomes more easy to gather and analyze collected data, integration of those systems in the daily maintenance processes offers a lot of opportunities (e.g. predictive maintenance). The example that the use of technology contributes to higher labor productivity, safety or quality, are numerous. The need for more ICT within the maintenance organization directly relates to the trend for a higher dependence on technology.
Tightening of regulation and need for compliance.
page | 19 The development of (new) regulations and standards in the Netherlands has serious consequences for the maintenance sector in terms of products, services and processes according to the NVDO reports. The impact of this trend on maintenance is very present, since ‘errors’ are less and less permissible and the maintenance professional is expected to be aware of all laws and procedures. This encourages the need for certification of the organization as well as the individual employee as much as possible. Having your norms and standards in place is important in order to stay a valuable partner for your client.
Influence of shareholders and investors.
One of the most fundamental trends identified within the maintenance area is the increasing pressure on the budget. This is due to the growing influence of shareholders and investors on many organizations. Since they concentrate on strong profit growth and efficiency, business operations and strategic decisions are on top of mind of shareholders and investors. Moreover, they have the power to dictate cost reduction programs and limit capital expenditures. Unexpected breakdowns and associated costs are not allowed. Meanwhile, respondents of the NVDO survey recognize maintenance still has to cope with the image of being a cost center. To deal with those facts it becomes increasingly important for ambitious managers to come up with a solid business case, wanting to improve their maintenance department. This means that convincing the right people with a business case can lead to space for investment. Capital expenditures (CAPEX), next to operational expenditures (OPEX) are of vital importance for maintenance (e.g. modern assets, innovations in inspection techniques, development of IT etc.). These investments require robust information to build the business case upon. The current technologies with respect to measuring and storing of data reached a relatively high level, the challenge lies in the selection of adequate data and analysis of data (Blok, 2009).
To summarize; the above trends show a demand for maintenance to develop in a broad sense; stronger integration with the business – manage the issues with the assets’ lifecycle – handle the drainage of technical knowledge – operate more efficiently by developing the IT system – operate more safely and reduce the risk for people and environment – decrease unexpected cost, limit capital expenditures and learn to build the business case.
Under these circumstances maintenance applications have changed from reactive maintenance to a more proactive approach. Formerly maintenance staff performed maintenance after failure occurrence, nowadays preventing failures by performing proactive maintenance is gaining ground (Cakir, 2011). The tendency of applying less reactive maintenance and moving towards a predetermined form and condition based approach is described in the three following trends
•••• a decrease in reactive maintenance
•••• an increase in predetermined maintenance
•••• an increase in condition based maintenance Reactive maintenance.
page | 20 Therefore it consists of unplanned activities and sometimes crisis management is required when an asset fails. The reason of the failure is diagnosed first, after which maintenance is performed. According to Mobley (2002) the reactive character leads to inefficiency due to variability in costs and organization of maintenance (e.g. spare part inventory, repair, cleaning etc.). Next to that, by challenging the due date of a certain asset, the risk increases since possible hazardous situations are not detected. This is in sharp contrast with the emerging trend to diminish risk to a minimum against societies’ critical attitude. In addition, this form of maintenance typically adds to the irregularity in the maintenance organization and, above all, deviation in (unexpected) maintenance cost.
On the other hand, reactive maintenance eliminates ‘over maintenance’. As such, there is no difference between immediate and deferred maintenance except timing. If the failure cost of this unscheduled maintenance is not higher than cost of proactive maintenance and safety and uptime are not critical issues, the application of reactive maintenance could be the most economical way of utilizing an asset or component optimally. It could be useful for simple non-integrated assets if a breakdown is easily and cheaply repairable and it doesn’t cause any other failure.(Mobley, 2002)
Proactive maintenance – predetermined.
A proactive form of maintenance that is based on scheduling is called predetermined maintenance. In its purest form, this comes down to act without taking the actual condition of an asset into account. Time or time since previous maintenance is the only criteria to execute maintenance. (Mobley, 2002). This concept is also known as periodic, planned or preventive maintenance. The goal is to decrease unexpected failures by periodically performing maintenance or inspections. It is not possible to eliminate every random failure in any case and fully rely on this concept; a certain risk is inevitable. To control this risk it is of importance to be aware of the possible failures and its additional consequences. The benefit can be found in the management of the activities on forehand, scheduling of required labor and increased clarity about the demand of spare parts. Needed spare parts are determined earlier and are acquired in time, and it decreases the number of breakdowns which reduces down time. Although this approach reduces failure risk and down time, costs related to over-maintenance and spare parts increase. (Dekker, 1996)
Proactive maintenance – condition based.
page | 21 interference and downtime. Compared to predetermined maintenance spare parts and unnecessary intervention or over-maintenance can be reduced.
2.4 | theories to improve
The previous paragraph revealed the urge for development of the maintenance organization. According to Swanson (2001) preventing your system from failures requires more than only applying a reactive strategy. Available techniques and theories accepted in literature and with reference to maintenance are presented now. The area of interest and desired goal is described.
FMEA.
The function of FMEA (Failure Mode Effect Analysis) is to select components that are responsible for a certain failure. This is realized by analyzing the effects in detail when breakdowns occur. To learn from a failure by recognizing the behavior and identify the so called failure mechanisms (issue that causes a certain failure) becomes relevant knowledge. It is used to enable preventive maintenance. The acquired knowledge is input for matching the required maintenance to the most critical components. An extension is also described in literature; FMECA, in which the component Criticality is added. Criticality in this context means the chance of a particular failure and consequences are also taken into account. (Tinga, 2010)
RCM.
Reliability centered maintenance is used to select future maintenance jobs on a preventive basis. In combination with FMEA consequences of a possible failure are identified. Thereby, RCM delivers a decision tool utilized on a component level. The ultimate goal is to increase plant reliability by maintaining the components that probably present the highest risk for reliability. (Tinga, 2010)
RBI.
Risk Based Inspection mitigates potential risk and is therefore frequently used in the oil and gas industry. The procedure for RBI is to identify dangerous assets, components or processes at first. Secondly the chance of failure is determined. The maintenance organization will benefit from the delivered inspection programme. (Tinga, 2010)
TBM.
page | 22 Figure 7: Schematic representation of the failure behavior in a 'Bathtub curve'
PAM.
Predictive Asset Maintenance focuses on the prediction of future need for maintenance or inspection. This is done in order to prevent from failing. It can be beneficial to apply condition monitoring to some assets or components. Since it is not feasible to apply PAM to each asset it is important to define the criteria. For example, PAM might be adequate when: an asset is of fatal importance to the process – an asset causes a high risk (e.g. safety, possible hazard etc.) for the employee or environment – a total breakdown is too expensive to replace. The acquisition of good quality data, and analysis is required to make a solid prediction. The ultimate goal is to define maintenance tasks that can be applied before the expected failure. (van Horenbeek, 2013)
2.5 | maintenance performance
Literature has extensively addressed maintenance performance. From literature it becomes clear that there is not one way to measure the performance of maintenance. This is confirmed by Murthy (2002) who also states that there are several things with regard to maintenance performance that are unclear. In both literature and practice there is vagueness about what to define as the maintenance metrics, how to communicate maintenance performance throughout the organization, and how to align the performance with objectives. Nevertheless, on a strategic level three parameters are common practice. Responsibility of maintenance is focused on:
•••• support towards operational excellence by keeping assets available;
•••• preventing from incidents in terms of safety, health and environment;
•••• and finally, to control the costs of maintenance.
page | 23 De Groote (1995) points out that performance of maintenance is hard to determine in absolute values. The reason for that is because maintenance is a logistic function integrated into a production process. Therefore parameters for performance must be defined in relative values, i.e. through ratios. An explorative examination of maintenance performance is provided.
Operational excellence.
The performance indicators that are related to a plant and its operational processes contribute to operational excellence. An overview of the PI’s (Performance Indicators) described in literature and associated authors are shown in figure 8.
Figure 8: Maintenance performance indicators related to operational excellence
OEE −−− Availability −− −− Speed −− −−− Quality
A technical ratio discussed by De Groote (1995) is OEE. The ratio indicates to what extent equipment is utilized effectively and can be used for internal or external benchmarking. This performance indicator is commonly used in a production sector of an organization and is calculated as follows:
OEE =
Availability is about the time an asset is technically available for production. The total time is divided in a part needed for production and the part when an asset is down for instance due to a breakdown. Typical values for availability are industry specific and vary generally between 85% and 99,5%. Costs of maximization of availability have to be earned back in terms of output.
Speed indicates the production amount per unit time, also called production rate. And quality is an indicator about the output of the system and the degree of rework that is needed. Each part of the formula is calculated separately:
page | 24
Downtime
Closely related to availability is the ratio of downtime. Downtime is the actual time the equipment is down for repairs or changeovers. Normally downtime is unwanted since this time cannot be utilized and leads to production loss. It is calculated by De Groote (1995) as:
Downtime ratio = 6 $ ! 7 $
8 9 ℎ , 9 9
Technical availability vs. commercial availability
A technically available system means the system is ready for operation, which does not necessarily mean that one needs to operate it. Richwine (2004) introduces the term commercial availability, as the name suggests it is depending on the commerce, or customer. It indicates the percentage of time the asset is available when utilization is demanded. There is stated that numerous utilities companies use the term commercial availability but there is no standard definition for its calculation. Moreover, the study demonstrated one third of UK’s utilities companies utilized the term, but none calculated commercial availability in the same way.
Richwine points out the indicator commercial availability is used more and more in the utilities industries. Due to heavy fluctuation in the energy prices it is not always profitable to turn on the installation and generate power. Whilst production capacity is relatively high compared to the average utilization of a plant. Therefore, under these circumstances, the use of commercial availability gives a better indication of maintenance performance.
MTBF −−− MTTR −− −−− Reliability −−−− Failure frequency
A measure of maintainability is Mean Time To Repair. When something fails and reparation takes long it is an indication for low maintainability. It is calculated as the average time an asset is down (Parida, 2007) :
MTTR =9 ! , ! ! , 7 $ 9
Mean Time Between Failure is an indicator which says something about the behavior of a failure. It is of great value when applying proactive maintenance. MTBF is calculated simply (Parida, 2007):
MTBF = ! , @ ℎ 9
! , 7 $ 9
page | 25 Reliability = A ! $ℎ ,
A ! , 9 100%
The failure rate is dependent on the failure frequency and the average time it takes between two failures. So, if the MTBF is already calculated, the failure rate is calculated by taking the inverse of MTBF (De Groote, 1995; Parida 2007):
Failure rate = 1 BACD=
/ ! , , 9
A ! , 9
Safety, Health and Environment.
Maintenance carries responsibility for the people and the planet by reducing the risk of possible failures. The environmental and employee safety is one of the tasks a maintenance department is taking care of in all companies within the resources industries. This is realized by ensuring equipment is safe for operators to work with and no environmental damage (e.g. explosion, leakage) will occur.
For the health of employees and the surrounding inhabitants is it of vital importance organizations operate safely. (Parida, 2007) The environment shall not be exposed to possible leakage of toxic and harmful substances. The reputation of companies, their partners and stakeholders is in the hands of maintenance organizations. Performance on topics as safety plays a significant role towards the manufacturing domain of the organization. Parida stresses that manufacturing is depending on the plant’s capacity in order to meet the delivery schedules, throughput, quality and cost. Furthermore, the ‘license to operate’ depends on the compliance to safety, health and environment (SHE) policies. All in all an appropriate strategy towards SHE is required to adapt to operational excellence. Performance indicators provided by literature are shown in figure 9.
Figure 9: Maintenance performance indicators related to SHE
page | 26 Figure 10: Accident ratio pyramid (Heinrich, 1941)
Heinrich defined the major injury as an accident that resulted in fatality or a disability of the employee which caused lost time due to medical treatment. Minor injuries required only first aid and still lead to lost time. The incidents or near misses, according to the definition, do not have direct consequences. Heinrich expects there is a relationship between the number of near misses (300) resulting in minor injuries (29) and major injuries (1).
Nowadays, for companies it is mandatory to report on injuries that occurred on the plant. For instance, this is done by keeping track of injuries and report conform to the OSHA frequency index. This represents the incident rate per 200.000 hours worked, and is calculated as follows:
OSHA Incident rate =/ ! , H 9
A ℎ 9 $ 7 200.000
Common values vary between industries since during some jobs people are more exposed to possible hazards or are more labor-intensive.
Maintenance cost.
As explained earlier in paragraph 2.2 maintenance costs represent a high share in the operational cost. The same applies for the total life-cycle cost of assets, which constitutes mostly of maintenance cost. Additionally, it is proven that the design of an asset is of significant effect on the maintenance cost. To have a stake in the design of assets, by means of system requirements, is of vital importance for maintenance. (Parida, 2007) An overview of the performance indicators provided in literature and associated authors are shown in figure 11.
Figure 11: Maintenance performance indicators related to Maintenance costs
page | 27 Either direct cost of maintenance over the added value of production or maintenance cost as % of the asset replacement value is recommended by De Groote as primary indicator to judge maintenance cost. This is calculated as follows:
6 ! 9
, or
B 9
K ! , 99 9 100%
The asset replacement value (ARV) represents the cost of replacing the total asset base a maintenance department is responsible for. In the asset intensive industries the ratio of maintenance cost as % of ARV is an ingenious indicator. Essentially it is meant as a generic indicator to assess maintenance performance on the cost side (Jusko, 2013; Kumar, 2013). However, the value of assets is rather industry specific. Since the asset replacement value is hard to determine maintenance departments calculate the replacement value on their own way according to Jusko (2013). Three different ways of calculating ARV are found and is explained as:
i. Based on the current price of acquisition and construction of such an asset (which basically comes down to a rough estimate)
ii. Based on the current value on an asset on the financial balance sheet (which changes for each individual asset from time to time due to depreciation)
iii. Based on the value for which the asset is currently assured.
Maintenance cost per unit
In the same context maintenance cost is related to the unit of which the output consists. For instance, the oil industry measures maintenance cost related to the number of barrels produced; utilities in kWh produced; and chemicals in tons produced. The drawback of these measures is the inability to compare cross industry.
CAPEX
Total maintenance costs exist out of operational expenditures (OPEX) and capital expenditures (CAPEX). Capital expenditures are defined as the amount spent to acquire or upgrade productive assets. Regarding maintenance this concerns investment in (new) machinery for production and also equipment for inspection or maintenance purposes. Like all other business, development of business units like maintenance comes with a price tag. Mobley (2002) states that launching improvement programs will cause initial increase in costs as a result of accelerated activities in the beginning - and besides, postponed performance increase. Likewise, it takes time to build a team, train people, implement new processes and incrementally change culture. However, Mobley (2002) stresses it is important to proactively invest in maintenance. The long-term payoffs will overwhelm initial investment. Mobley describes this in three ways. To the extent that asset downtime can be reduced and cost from lost revenues can be saved. Secondly, by enhancing asset performance, throughput can be maintained and production quality is improved. Thirdly, an adequately maintained asset will increase its lifetime and reduce the CAPEX.
OPEX
page | 28 operation, asset installation and generic costs. For instance, the replacement of parts, labor of inspections and maintenance activities.
Conclusion.
To summarize, the important aspects on a managerial level that are also relevant for the empirical research are:
• From an operations point of view, the process uptime which is influenced by the asset availability that maintenance is able to provide.
• The risk and safety parameter; number of injuries per hours worked
• And from as cost perspective the maintenance costs. In order to make a cross industry comparison there maintenance cost can be compared to the replacement value.
Regarding the empirical research further argumentation is provided in paragraph 3.2 to make a selection of PI’s that will be assessed in order to determine maintenance performance. The selected PI’s are in correspondence with the first part of the research model.
2.6 | maintenance strategies
Literature presented in paragraph 2.3 already explored reactive maintenance − to be classified as corrective maintenance − and the tendency to focus on proactive maintenance − to be subdivided in predetermined/preventive maintenance and condition based/predictive maintenance (Niu, 2010). In several academic articles corrective, preventive and predictive maintenance are classified as a strategy as part of the maintenance strategy (Blanchard, 1995; Tsang, 1995; Swanson, 2001; Duffuaa, 2001; Ahmad, 2012)(figure 12). On high level it is elaborated on how these strategies are applied and how business is affected.
Figure 12: Application of reactive and proactive maintenance is part of the maintenance strategy (Tsang, 1995; Niu, 2010; Ahmad, 2012)
Breakdown or corrective.
As Niu (2010) states, corrective maintenance can be defined as maintenance which is undertaken after a breakdown or when obvious failure has been located. The ‘correction’ or repair can either be executed immediately or deferred. Corrective maintenance at its best should be utilized:
• in non-critical areas;
• where cost of capital are small;
• consequences of failure are limited;
• where there is no immediate safety risk;
page | 29 Mobley (2002) provides insight in the use of corrective maintenance and states that few plants use a true run-to-failure maintenance strategy. Basic preventive tasks are always performed (i.e. lubrication, machine adjustments). With managing maintenance with corrective maintenance assets are not rebuilt, neither major repairs are performed until equipment fails.
Predetermined or preventive.
The definition of predetermined/preventive maintenance comes down to the planning and execution of predetermined maintenance intervals and tasks. The status of the asset is assessed by means of inspection. The intervals and tasks are intended to reduce the assets’ probability of failure or degradation. Predetermined maintenance is scheduled without the occurrence of any monitoring activities. Scheduling for example, can be based on prescribed criteria about the number of kilometers that has been used, the time an asset is in function, the usage etc. (Niu, 2010)
Condition based or predictive.
Contrary to predetermined maintenance, condition based maintenance and predictive maintenance do not use predetermined intervals and schedules. The condition of components is monitored periodically or continuously in order to gather data about the current status and behavior. A dynamic schedule for maintenance tasks is the outcome.(Niu, 2010)
In the case of predicting a failure which can be prevented by applying maintenance previous to the failure, failure patterns are necessary Garcia (2006) says. If the evolution of the life of a component is close to the pattern of some failure mode previously developed, it is possible to estimate the current health condition by reference to the end point of this failure pattern.
Figure 13: Indicative Failure pattern (Garcia, 2006)
Being able to identify the failure on the basis of gathered data is not enough. Garcia explains, in order to predict a failure, the failure patterns have to be developed on component level, and for that, the history of failures has to be analyzed. Based on the failure pattern it is possible to predict time remaining till failure as shown in figure 13. Thus, proper analysis has to be carried out to make a prediction.
page | 30 Since the strategies cannot be implemented as a standalone strategy, corrective, preventive and predictive maintenance can operate next to each other. Depending on the situation informed choices can be made to decide whether the asset or component is equipped with a certain maintenance strategy. Each strategy has its own advantages and disadvantages. These are summarized by Cakir (2011) in figure 14.
Figure 14: Advantages and disadvantages of the maintenance strategies (Cakir, 2011)
page | 31 Figure 15: Optimization of maintenance cost by an optimal mix of maintenance strategies (Mobley, 2002; Cagle, 2003)
In summary, the model in figure 15 leads to the following conclusions:
• More proactive maintenance will lead to less corrective maintenance;
• Maintenance cost can be optimized when an optimal application of corrective, preventive and predictive maintenance is found;
• Too much proactive maintenance can lead to higher cost;
• Therefore, in terms of efficiency, it requires more intelligence about how much maintenance is exactly needed in each situation (e.g. for each individual asset), in order to find the optimal cost.
Drivers.
Possible drivers that are an incentive to develop maintenance have been investigated by Ismail (2012). An empirical study amongst hundred thirty four executives of large companies resulted in typical drivers which represent the motive to change the current maintenance situation. Development of maintenance could, for instance, be the investment in monitoring equipment to acquire data or training of people to become more specialized in maintaining. The results out of the study are presented in figure 16.
page | 32 The most important driver for maintenance related to management functions is the pressure on reduced operational budgets. It appears that maintenance budgets for operational expenditures are decreasing due to pressure of shareholders and investors. While, at the same time, respondents remark maintenance cost increase due to an increase in life-time-extension programs.
More and more the maintenance department is taking responsibility for the return on assets. Since maintenance has a high stake in the availability and maintaining a certain production output, maintenance is partly responsible for the financial value of the asset base.
Next to the reduction on operational budgets, also the capital budgets are being reduced, and therefore are a driver to further develop maintenance. The hypothesis is that improved maintenance control contributes to an increase in asset lifetime.
The cost of materials that are used for replacements are rising. The rising cost are a push to improve maintenance performance. Respondents of the survey expect that by developing maintenance material cost can be lowered.
Overall the asset base of asset intensive industries is aging. To cope with this fact maintenance should apply intelligent solutions to overcome extensive cost.
Conclusion.
To conclude, the discussed maintenance strategies and drivers to develop maintenance are input for the research model. The subdivision of strategies by Tsang, 1995; Niu, 2010; and Ahmad, 2012 is a an approach which most probably is recognized by respondents of the research and therefore is applicable to include in the empirical research. The presented drivers are specific and are relevant in an maintenance context. Therefore these drivers are, in principal, appropriate to test on presence in a business situation. Additional motivation for the design of the research model is explained in paragraph 3.2.
2.7 | maintenance capabilities
In paragraph 2.4 a variety of techniques and theories has been presented which can be applied by a maintenance organization. Supported by literature it can be said that implementation of certain techniques and theories can enhance maintenance performance. However, the question remains what defines a mature maintenance organization. Van Horenbeek (2013) concludes: the use of prognostic methods in maintenance in order to improve in the broad sense is receiving more attention over the past years. However, the use of these techniques in maintenance and required capabilities is still an uncharted territory.
Capabilities.
Even though, some rather general and more specific capabilities are found in literature. The capabilities are all directly related to maintenance.
page | 33 In the search for guidelines for implementation of predictive maintenance McKone (2002) states that the use of condition monitoring, and, application of analysis on gathered data, are essential elements for predictive maintenance. Which is confirmed by Tsang (1995); according to him maintenance need to be capable of capturing data and perform analytics on such data.
Another aspect is the time of failure that can be modelled by intelligent software, based on extensive data. Which, was also being explained by Garcia (2006) in paragraph 2.6 (use of failure
patterns). The output of the modeling is a recommendation about an intervention in the system.
McKone stresses that a prediction does not provide the desired result when sufficient time to intervene is not available.
Capability Maturity Model.
Outside the domain of maintenance a generally applicable model was found in literature of Moignard (1995) who developed the Capability Maturity Model. The model is built to assess the level of software-development of an organization and consists out of five stages (figure 17). The stages are iterative, that is, no stage is skipped, but an organization can vary in the amount of time, energy or cost spent at each stage. Furthermore, the stages are cumulative, which means organizations are still capable of performing the underlying stages at each moment.
Figure 17: Capability Maturity Model; originally used to assess the maturity of software-development (Moignard, 1995)
Five stages are identified starting with, and described as:
I. Ad Hoc; These are the initial steps which are quite chaotic, problems are solved after they occurred. This is a level each organization is capable of.
II. Repeatable; In this level the organization is professionalized to an extent that lessons are learned from events that previously occurred. This is the beginning of making decisions based on experience.
III. Defined; Most of the important or core processes are standardized. Tools, techniques and templates are being installed in order to become more effective.
page | 34
V. Optimizing; Organizations are able to fully control all situations, there is an ambition and active search for efficiency and fine-tuning.
In order to utilize the model the author points out the model is scalable, which makes it applicable to an enterprise as well as a department or work team. The model works well as a tool to assess and summarize the current state, to recommend further steps and generate discussion. As an improvement practitioner the model can be used as a checklist or encourage mutual exchange of strategic ideas.
Conclusion.
In order to test the maintenance maturity no complete maintenance model is found in literature. Therefore, a general maturity model will be coupled to the capabilities proposed by the authors in this paragraph. Further motivation can be found in paragraph 3.2.
2.8 | enablers of predictive maintenance
In previous paragraphs the required capabilities a maintenance organization should have in place were discussed. However, no detailed description is provided on how predictive maintenance could be enabled within a company. Since the application of predictive maintenance is relatively new to the business, no empirical evidence is found regarding the successful application of predictive maintenance. In the search for enablers of predictive maintenance which are proven in practice, an auditing model is presented. Bana e Costa (2011) propose a multi criteria model that audits a predictive maintenance strategy. Shown in figure 18.
Figure 18: Auditing areas on which the application of predictive maintenance is audited (Bana e Costa, 2011)
A udit ing area s
STRATEGY: Account s for the exist ence of a well-defined PAM strategy in accordance with t he maintenance and st rategies, as well as for t he influence of PAM on the implemented system
ATTITUDE: Regards the behavior of t he personnel directly or indirectly involved in PAM
RESOURCES: Considers t he level of integration of the predict ive information system with other informat ion syst ems, as well as the availability of hardware and devices t o be used in predictive data
HUMAN RESOURCES: Considers t he job roles, responsibilities, incent ives, and training and organizational aspect s of personnel involved in PM
RECORDS: Regards the process and quality of collecting PM data on failures history, physical resources, etc. PLANNING: Care about the activities t o be developed, t he sequencing, the materials and the skills required for PM
SCHEDULING: Is concerned with t he details regarding various scheduled periods, PM procedures required, estimated job t imes and when the equipment is available for maintenance
WORK ORDERS: Considers t he availability of documents authorizing the completion of a specific task BUYS: Cares about purchasing policies and related aspect s
STORE/ STOCK: Is concerned with storage policies, such as t he efficiency of the layout, the use of bar codes, the locat ion of component s, etc.
PROCEDURES: Account s for the level of use of standards, development of guidelines and procedures for carrying out PM activities
CALIBRATION: Is concerned with t he reliabilit y of PAM devices for ensuring quality in the calibration programme TECHNICAL SKILLS: Is concerned with PAM technical issues, e.g. the definit ion and use of alerts and alarms in PM
EFFECTIVENESS: Account s for the level of f ulfillment of objectives established in the strat egy and the degree of PAM user sat isfaction; also, it considers the relationship bet ween PAM and the ot her maintenance policies
page | 35 The auditing model is based on a questionnaire with over hundred seventy questions asked to people in the management level, technical and consulting staff of a hospital. It concerned people who were directly involved by a predictive maintenance program. The outcome of the questionnaire is a list of fifteen auditing areas. Looking at the auditing areas there can be concluded it is a rather broad description of all possible enablers that need to be in place before successfully predictive maintenance is executed.
Conclusion.
