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Maintenance Performance: Improving Maintenance Performance in Pulp and Paper Mills

Back in 1998, research by the BCG Group on asset productivity demonstrated that improving fixed assets productivity is the most powerful mechanism to improve shareholder return [1]. Further studies ha…

Back in 1998, research by the BCG Group on asset productivity demonstrated that improving fixed assets productivity is the most powerful mechanism to improve shareholder return [1]. Further studies have shown that maintenance improvements have a high Economic Value-Added (EVA) potential as illustrated in Figure 1.

This article reviews the maintenance improvement tools currently available to pulp & paper mills to tap that potential.

Maintenance analysis and the maintenance management reference plan

Building a maintenance plan without knowing exactly what the current status of maintenance is, is like going hiking without knowing where your starting point is. It is not enough to know what the target is, because the means to achieve the target will depend on what the current status is. Therefore an accurate Maintenance Analysis is always required before conducting any major improvement. A typical analysis performed by experienced auditors will yield valuable information about the efficiency of the maintenance organization, skills, systems and material means. It can reveal issues which should be addressed prior to any other maintenance improvement takes place.

The analysis should include a benchmarking study, in which the maintenance organization is benchmarked against World Class Maintenance (WCM) practices. Good benchmarking can reveal additional improvement opportunities, sometimes even better than the original plans were. Benchmarking results can be summarized as shown in Figure 2.

The original improvement targets should be checked against these benchmarking results so that any unreasonable targets can be eliminated. Note that not all companies can and should be at the WCM level. In theory, any mill can reach this level but very often the most cost efficient solution is somewhere lower. Typical reasons for this could be the location of the mill, the age of equipment, the type of production and many other limitations.

Once the analysis has been conducted, the next phase is typically to create a long-term (4-6 years) Maintenance Management Reference Plan. This plan describes the planned targets for the maintenance organization and how to develop maintenance so that the targets can be achieved. All maintenance improvements should be treated as projects with a clear time frame, targets and a management group where other departments such as operations and HR are also represented.

Key Performance Indicators

Key Performance Indicators (KPIs) are the most important measures for maintenance and operations. They are derived from the Maintenance Management Reference Plan and are the basis of any continuous improvement project as illustrated in Figure 3.

Without well-defined and accurate KPIs, it is impossible to track maintenance improvements. Typical maintenance KPIs used include:

Overall Equipment Efficiency, OEE (%)

Maintenance cost ($)

Maintenance cost/produced ton ($/ton)

Lost tons due to maintenance (tons)

Maintenance overtime (%)

Maintenance backlog (weeks)

Emergency work orders (% or #)

It is always better to start measuring only a few indicators and to set up a good system to provide accurate and consistent measures. Once the systematic monitoring and gap analysis of KPIs are working well, you can add more indicators.

Overall Equipment Effectiveness (OEE) measurement is the most powerful technical KPI for a pulp or paper mill. It quantifies the overall productivity of the plant and helps to identify inefficiencies in three main categories: equipment availability, equipment speed and product quality. A well-established OEE measurement system will produce a lot of useful information for maintenance about the equipment reliability and helps to identify the most important improvement opportunities.

Preventive Maintenance

Preventive Maintenance (PM) is one of the oldest and easiest ways to improve maintenance, and today it still remains the most important tool. Unfortunately, its importance has sometimes been overlooked because of new trends that may or may not endure the test of time. Many maintenance supervisors believe that PM tasks take too much time and that they do not have enough manpower to perform all the inspections required.

PM consists of periodical inspections, service and clean-up of equipment and replacement of parts, in order to prevent sudden failures and process problems. Like any of the other maintenance modes of the Maintenance Improvement Path illustrated in Figure 1, PM requires some basic asset management tools to cover the safety and environment, organization skills and training, human resources, spare parts and supply, and financial control requirements. Then, recognizing that all equipment cannot receive the same level of attention, because maintenance resources are limited, the preventive effort should begin with prioritizing the equipment. Ranking by priority will help determine which equipment to select for periodic maintenance.

Time-based job plans are further drawn up using maintenance standards for material selection, work estimating, spare parts control, lubricant control and safety, so that the time the actual work takes is minimized. Job plans are continuously improved by accurately closing PM work orders, followed by conducting analysis on the work orders. Neglecting this opportunity to optimize results in an overloaded maintenance department that performs randomly neglected PM tasks, and as a consequence, mill efficiency decreases.

Predictive Maintenance

Predictive Maintenance (PdM) offers increased equipment reliability and sufficient advance information to improve planning, thereby reducing unexpected downtime and operating cost.

To promote the early detection of abnormal conditions through PdM, it is essential that common objectives be set for the maintenance and production groups and that the ownership of the equipment, the roles and responsibilities as well as communication and reporting be clearly defined.

The first step in preparing to conduct the diagnosis is to identify the physical parameters to be monitored and the corresponding Predictive, Testing & Inspection (PT&I) technology to be used. Having defined the engineering limit for the physical parameters so that a problem can be detected during routine monitoring before excessive damage occurs, a certain number of diagnosticians should be trained and a comprehensive diagnostic system established. On that basis, diagnosticians will then be able to perform measurements, and to analyze and collate the results.

If the equipment diagnostic indicates that a repair is required, the repair will be planned and implemented, and the deterioration should be assessed. To refine the PdM approach, integrating the PdM techniques with the Work Management process will further enable the asset management strategy to be driven by condition data for improved maintenance decisions.

Proactive Maintenance

One of the main elements of Proactive Maintenance is Reliability-Centered Maintenance (RCM). Developed in the early 60’s by the US Civil Aviation to ensure greater safety and environmental integrity, RCM is now used throughout the industry. According to John Moubray [2], “RCM is a process used to determine the maintenance requirements for any physical asset in its operating context.”

Whether it is rigorous or streamlined, RCM uses Failure Mode Effect and Criticality Analysis (FMECA) to determine the best form of maintenance required by a piece of equipment. In other words, FMECA looks at the equipment functions, functional failures, failure causes (the modes), and consequences (the effects). The failure consequences and their criticality are analyzed by taking in account the safety, environment, availability and cost impact severity, coupled with the likelihood of occurrence and the level of detectability.

Using the FMECA results and taking the technical history into account, equipment maintenance policies can then be formulated. Technical history is an essential part of the planning process and explains why Work Order data should be validated. V
alidated information includes:

The Mean Time Between Failures (MTBF) which is calculated to establish the frequency of failure finding tasks, is used to help determine whether scheduled maintenance is cost effective in the case of failure modes that have operational or non-operational consequences only, and to help establish the desired availability of a protective device.

Existing Work Orders are also analyzed to determine the accuracy of the information collected. Any adjustments to the feedback method are made at this time.

Total Productive Maintenance (TPM)

The ultimate phase in maintenance development is to take a reliability-driven approach. This may be obtained using all or some of the TPM concepts. A mill embarking in TPM should carefully and thoroughly prepare the foundation for the TPM program. The next step is to foster a working environment that boost employee morale and promotes education.

Success is ensured by carrying out selected activities designed to achieve the targets shown in the Maintenance Management Reference Plan as well as by embedding the TPM activities firmly in the culture and continuing to make them more effective.

Key ingredients include:

Building strong teams at every level

Creating promotion opportunities for staff

Team building is based on the recommended approach for TPM activities, which emphasizes a continuous improvement approach through the CAPD cycle (Check Act Plan Do) that complements focused improvements as illustrated in figure 4

Continually revising goals upward

Setting new challenges

Having focused, continuous and concrete measurements plus clear baselines and documentation of results

A case study

The mill we use as an example has a deinking plant, three paper machines and several converting lines. ABB has been responsible for all maintenance according to the full service agreement signed several years ago.

The OEE on the paper machines has been one of the maintenance KPIs for years. The results show that using traditional tools (such as preventive maintenance, rigorous work order management, and inventory optimization), ABB has been able to assist the customer in reducing maintenance costs while at the same time improving production efficiencies. In order to continue improving new approaches were required.

As part of a joint project, the customer and supplier teamed up to improve reliability in 2002, and is an ongoing project. One representative from each organization teamed up to lead the project while other resources performed the tasks.

One of the first priorities was to define and implement the KPIs for reliability. Each KPI includes a formula with units, frequency of measurement, process areas where the data is collected, data source, identifying a responsible for data collection and reporting, and effects on reliability. The KPIs are:

Mean Time between Failures (MTBF). The failures are reported by maintenance and analyzed with an On-Line Analytical Processing (OLAP) tool called Maximo Analyzer [3]

Preventive maintenance compliance (actual versus planned preventive maintenance work)

Emergency work (emergency work hours versus all maintenance hours)

Mean Time To Repair (MTTR)

Maintenance cost ($/ton)

Overall Equipment Effectiveness (OEE) (%)

Completed Root Cause Analysis cases / month

Planned shutdown maintenance compliance (completed versus planned shutdown work)

Another task was to improve failure reporting. New failure codes and more rigorous reporting were introduced while new electrical production log books were developed.

Equipment criticality analysis has been one of the basic tasks in the project. Using streamlined RCM methodology, the most common failures were identified from failure history in Maximo [3] and other data sources. On that basis, the preventive maintenance plans were designed or updated to prevent such failures.

Weekly meetings between production and maintenance were improved. Root cause analysis was included in the agenda. Causes of production losses were discussed and the potential reasons were documented.

Machine operators are now participating in preventive maintenance. Their tasks include lubrication and simple checks based on standardized lists. The aim is to encourage TPM-oriented ownership of production equipment.

Conclusion

Maintenance is one of the largest controllable costs in the pulp & paper industry. It is also a critical business function that impacts commercial risk, plant output, product quality, production cost, safety and environmental performance. Although improving maintenance is not difficult, it does require common sense and a systematic approach. In most cases technical solutions are only part of the solution; employees can contribute in significant ways to the success of the program and should be provided coaching.

Jean-Pierre Bricteux is Maintenance Engineering Manager and Jukka Tuomela is Asset Management Services Manager for ABB Inc.

Bibliography

[1] Ron Nicol and Philippe Amouyal, the Boston Consulting Group (BCG), Discussion Paper: “Asset Productivity: The Next Wave”, December 1998.

[2] John Moubray, Reliability-centered Maintenance, 2nd Edition. New York, NY: Industrial Press Inc., 1997.

Registered trademark

[3] MAXIMO is a registered trademark of MRO Software, Inc.#text2#