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Maintenance Matters: Productivity Measurement For Maintenance Cost Reduction

Labor productivity has a major impact on the cost of maintenance and few maintenance managers know the effectiveness of their crews. They should know and improve the conditions that affect labor productivity on their sites.

This article originally appeared in the October print issue of IMPO Magazine. To view the digital version, click here

Throughout my career, I saw — or rather felt — the various economic crises created by several factors from the 1970s oil crisis to the world economic crisis in 2008. The crisis periods and an increasingly competitive market always results in one common remedy: an enormous pressure to reduce costs. Without the proper precautions or criteria, this cost cutting may jeopardize business continuity.

Labor productivity has a major impact on the cost of maintenance and few maintenance managers know the effectiveness of their crews. They should know and improve the conditions that affect labor productivity on their sites. The way they design and implement their maintenance management processes directly impacts the productivity of the maintenance workforce. We will try to illustrate how our company, Quant, helped one customer to identify and remove barriers to improve the maintenance workforce productivity.

We will start by defining maintenance productivity as the ratio of the output to the input of a production system. With a given input, if output of products or services is higher, then productivity/ efficiency is higher. Efficiency is doing things right or it is the measure of the relationship of outputs to inputs and is usually expressed as a percentage.

In summary, the total productivity of the maintenance workforce can be divided into three factors:

1. Utilization: The elimination and reduction of nonproductive work such as time spent waiting, walking or being idle.

2. Performance: Increasing speed of task execution through a higher quality of employees, improved tools and working methods and planning and scheduling.

3. Quality: The elimination of unnecessary tasks using work flow and plans analysis, organization analysis, failure analysis, execution quality and equipment design-out.

Utilization X Performance X Quality = Total Productivity

Our study focuses on the utilization factor only. We wanted to identify the wasted time associated with maintenance tasks, for example, the time technicians lose having to move around unnecessarily in different areas of the plant or wasted time waiting for work permits, spare parts, tools, instructions and other documentation required for completing an assigned task. To be able to measure productivity, we adopted the work sampling methodology, which is a measurement technique developed in the 1930s by L.H. Tippet to analyze, classify and quantify work using instantaneous observations of work in progress taken randomly over a period of time. It is based on the laws of probability and to determine the proportion of the total time dedicated to the various components of a task.

To conduct a work sampling study, a large number of observations or snapshots are taken randomly and during each observation the condition of the worker is determined and recorded in a predefined category of activity pertinent to the particular work situation. Inferences are then drawn concerning the total work activity from the proportions of observations in each category. Based on these measurements, we conducted this study in various petrochemical plants in Brazil. For the study, the maintenance activities were divided into three categories: productive, support and nonproductive:

Productive: Working and Planning

This category includes adjusting, welding, positioning, cleaning, inspecting, assembling, analyzing, discussing execution, drawing sketches and a number of other activities.

Support: Watching, Walking and Waiting

Watching refers to supporting and serving as a stand-by, while waiting refers to time spent acquiring tools, materials, scaffolding, lifting equipment, work permits or instructions.

Nonproductive: Personal and Idle Time

Nonproductive time is classified as personal and idle time such as drinking water, coffee breaks, smoking and conversations not related to work.

The study revealed the following percentages:

• Working: 26 percent

• Planning: 11 percent

• Productive (Working + Planning): 37 percent

• Waiting: 27 percent

• Walking: 28 percent

• Nonproductive (Personal): 1 percent

• Nonproductive (Idle): 7 percent

Assuming a workforce of 100 people with an average labor rate of $40.00 per hour, these losses represent a substantial economic drain equal to $4.6 million each year.

The results of study were presented to plant management and interested parties and then working groups were created to analyze the causes of unproductive time and to propose plans for improvement.

These groups studied and suggested actions for each of the priority items. For example, for the “walking time” issue, the working group identified the following causes: logistics and improper layout, incomplete maintenance planning, deficiencies in internal transport, workers stretching lunch breaks, unavailability of tools, difficult access to productive areas, unavailability of scaffolding and lack of operators to issue work permits.

Several actions were suggested and implemented to eliminate and reduce walking time including reviewing standard work order preparation, reducing internal bus intervals, reviewing meetings schedule, inventing a mobile tool cart so that workers would not have to go to the warehouse and allowing tools to be left at work during breaks and at the end of the day.

After implementation, a new study was conducted with the following results:

• Working: 50 percent

• Planning: 10 percent

• Productive (Working + Planning): 60 percent

• Waiting: 17 percent

• In Transit (Displacement): 19 percent

• Nonproductive (Personal): 2 percent

• Nonproductive (Idle): 2 percent

With the results above, the losses were reduced by approximately $1.7 million per year.

In Summary

If we consider that the maintenance labor productivity benchmark for petrochemical industry is 60 percent, we can say that this company achieved their target. The results demonstrate the importance of monitoring maintenance functions in order to improve efficiency and productivity in manufacturing plants.

Jose Baptista is Development Manager, Reliability at Quant, a maintenance outsourcing provider. To learn more, visit www.