The lack of data and information on losses in productivity and service delivery in maintenance of industrial plants makes decisions to reduce losses difficult, or even leads to a wrong decision, costing much more for the company.
Historically (from 2009 to 2011), 31.5 percent of the maintenance cost was spent on labors (titanium dioxide plant – sulphate rote – Cristal Company). Identifying how the maintenance management system distributes the working hours for employees and the work order execution for each employee becomes crucial in identifying the losses and bottlenecks in the working day.
What is the wrench time level (the effective time that a maintenance employee is working “hands-on”) and what are the existing losses in the maintenance labor process in a titanium dioxide plant (sulphate route) at the Cristal company in Abrantes, Brazil.
Not knowing the level of workforce losses in maintenance services makes it difficult to develop an action plan aimed at potentially reducing maintenance costs by reducing time loss of the workforce in the maintenance process.
Objective of the Work
This project, using the Project Management Institute’s Project Management Body of Knowledge (PMBOK) global standard for project management, aims to identify and characterize the working day shift of maintenance workers (own and contractors) in a titanium dioxide plant (sulphate route). In doing so, the company will have knowledge of the losses and be able to develop an action plan aimed at reducing workforce time loss in the maintenance process, therefore increasing productivity and staff motivation.
Execution maintenance services within the work order process of companies is usually a centralized process coordinated by the planning area. It is the means used to manage (registration, control and distribution) man-hours in the plant to maximize its use and minimize the impact and cost required to work.
At Cristal company, titanium dioxide industry (paint pigment) - sulphate route, the work order execution flow (Figure 1) is computerized and begins with the opening of an occurrence. After analysis of the responsible area and checking for duplication, if data is correct, it is changed into a service request (SS). Then the respective area planner details the work order, specifying each activity required to meet the work order and linking skills and the estimated time for each activity. The work order is also comprised of interdependence between the activities so the software can do the weekly scheduled services and workforce distribution using either the program evaluation and review technique (PERT) or collaborative production management (CPM), which maximizes the manpower utilization forecast. Once the work order list for the next week is generated, planners send the warehouse a list of materials necessary for executing these scheduled work orders so the warehouse can deliver the materials to each field shop. The process enables supervisors and executors to identify any interference in the process, such as emergency work orders, failure in materials delivery, an equipment schedule not provided by the operator (clearance) for maintenance, or failed communication between maintenance and operation. By doing so, the system can run with maximization of resources.
Figure 1: Work order (W.O.) execution summary flow at Cristal Company, Brazil.
Although the titanium dioxide plant has a more efficient workforce management system, some losses exist in the process as:
Clothing change/moving to the job;
Filling in work permit;
Going to the bathroom in the morning/afternoon;
Displacement for lunch, snacks, water, coffee;
The maximum productivity achieved with the workforce at the Cristal titanium dioxide site is an efficiency of approximately 77 percent. According to the 2006 scholarly article by Oliveira, Silva S., et al, on a maintenance planning strategy for a leap in productivity, the benchmark for workforce efficiency, considering the international reference for maintenance of refineries and petrochemical, is 65 percent.
Measuring workforce efficiency, or the time the maintenance employee was working, also known as hands-on or wrench time, was done as a project using the methodology and knowledge of the PMBOK through the development of management plans following:
This was initially done in the plant and included a disclosure with the aim of the project details, a project team presentation for the people involved (director, managers, superintendent, supervisions and doers) and in a summarized way for the rest of the site via intranet, thus facilitating the project’s receptivity and knowledge. A questionnaire was done during disclosure meetings with the maintenance crew, with the goal of determining how the productivity was from a doer vision, as well as identifying some bottlenecks that could be influencing productivity.
For the measurement of each worker’s maintenance workflow step in the field, there were three possibilities for data collection:
Using the recorded data by maintenance employees in work orders. However, the data was analyzed and it was verified that it was not properly appointed.
Implementing time cards, with employees recording each step on the card for later analysis. This method was discarded since it added another document in the process (production loss) and would have the same problem as Item #1.
Monitoring random work orders on-site at a chosen area (Figure 2), consequently the monitoring of each employee across selected work orders, Cristal and contractors, for each activity from the beginning to the end of the workday.
Figure 2: Measurement time flow summary during work order (W.O.) executio on site
After defining the way to collect the data (#3 option), a spreadsheet was developed to record the collection of these data and to standardize the sampler’s collection so it was easier to type into the database (see Table 1).
Table 1 - Description of activities (execution and losses) followed in the field and their respective percentage
To make the data representative, a control was created to avoid concentration of the survey in the following points: weekday, the work order priority (emergency x urgency x normal), confined space and planned or unplanned work order. Regarding the amount of work orders to be sampled, it was determined that it would be the number of work orders corresponding to three months of labor workforce performing in maintenance, representing approximately 40,000 man-hours.
Analysis of Results
The data sampled in the field was registered in spreadsheets per production area and contractors’ skills (fitters, rubber and fiber, scaffolding, electrical and civil) that provide service for maintenance. A total of 50,250 man-hours was measured, spread among types of losses and execution (hands-on).
From an employee’s point of view, the top five losses were attributed to:
Work permit clearance process.
Activity details in work order need improvement.
Availability/delivery of materials in the warehouse.
Communication among planner, doer and operations before details work order activities need to be improved.
More electricians for work permit process need to be provided.
ANALYSIS OF LOSSES AS A FUNCTION DURING PART OF THE DAY
In Figure 3, which summarizes data collected from contractors and Cristal employees, the time of hands-on represents a total of 43 percent, consequently a loss of 57 percent. Also, the graph shows a greater loss in the morning (33 percent), where it was observed that this loss was related to the time of arrival at the shop, the toolbox meeting, the work order distribution by supervision, tools preparation, the work permit process, stopping to get parts and losses mainly due to displacements (see Figure 4). In the afternoon, which is usually the same work order continuity, so there is no need to open a work permit, the percentage of effective work (hands-on) is slightly higher than the percentage of losses. (25 percent vs. 23 percent, respectively). Displacement is the biggest reason for working hours losses (see Figure 4) and spare parts is the biggest reason inside the displacement.
Figure 3: Productivity and losses result in the morning and afternoon among maintenance staff and contractors
Figure 4: Losses percentage on a Pareto chart for maintenance own and contractors
Figure 5: Pareto’s loss percentage displacement - maintenance own and contractors
Figure 6: Pareto Work Permit percentage losses – maintenance own and contractors
There is great potential for reducing losses in working hours in a chemical plant of titanium dioxide by 22 percent through actions related to the organization/flow and working methods applied in maintenance’s everyday life.
Furthermore, planning is an important tool that maximizes productivity through the convergence of all involved to the same goal: work order execution in the fastest time possible to reduce losses.
Supervision is fundamental for gaining participation for productivity improvement through efficient distribution of work orders and monitoring of work execution.
Roberto Máscia has been a Mechanical Engineer since 1987. He received his Master’s degree in 2001 (developed an alloy against erosion), his MBA in 2009 (measured the maintenance wrench time) and Safety Engineer in 2010 (identified the consequence of lack of energy at a chemical plant).
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