Optimizer+ gives EMO confidence in the results of maintenance
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As a maintenance engineer with a penchant for numbers, it's hardly surprising that Peter van Dijk at EMO is particularly enthusiastic about the ability of Optimizer + to predict maintenance costs. “It's a great management mechanism for budgeting”. EMO performed a pilot for one of its conveying systems. The results were more than encouraging.
EMO is located in the Maasvlakte area on the outskirts of Rotterdam. The largest bulk goods and transhipment company in Europe for ore and coal is almost fully automated. Conveying systems of almost fifty kilometres in length operate continuously in order to transport the raw materials to and from different locations at the site. From one ship to another, or from the yard area to a storage silo or to a freighter that needs to be loaded. Or to the wagon loading area where the raw materials leave the site by train.
The majority of the company's operations are controlled remotely from a control room that most closely resembles a traffic control tower at an airport. The machines that deposit and/or dig up the raw materials around the site use GPS or other technologies to allow complete computer control.
However, not everything can be automated. Because the raw materials we work with at EMO can vary in terms of quality and composition. Sometimes a cargo is very wet and sticky. That can cause even more problems in frosty conditions. The ore can stick together as a solid mass if the bunkers used to load the wagons in the wagon loading area are full. It can sometimes take hours to get things working normally again. Time we can't afford because delays like this cost money.
The problem
EMO has every reason to keep plant availability and reliability as high as possible. “If a ship with 400,000 tonnes of cargo cannot be unloaded because of a fault in the machinery, we have a real problem”, says Peter van Dijk. He and his colleagues are all responsible for their own section of the plant. They keep a sharp eye on operations. Each fault is entered in the system and the availability of each item of plant can be monitored down to a detailed level.
When Peter van Dijk joined EMO a year ago, he and his colleagues in the maintenance engineering department drew up an initial analysis of eleven management aspects within the maintenance envelope. Their conclusion was that maintenance could be improved in four areas. The process used to create the maintenance concepts could be improved, modifications were insufficiently justified and EMO seemed not to learn adequately from faults. “Certain faults were found to re-occur on a regular basis. That's what you need to focus on as a company. Some of the faults had to be subjected to a Root Cause Analysis before the true problem could be identified.” In addition, Peter van Dijk and his colleagues wanted to clearly identify what preventive maintenance was required in relation to the risks.
Crucial system
At the beginning of this year, Peter van Dijk started up a pilot project together with his colleagues and MaxGrip in order to investigate the benefits of implementing risk-based maintenance. Optimizer+ was used to perform a risk analysis for one of the conveyor systems: conveyor number 121. Not the most fault-prone conveyor, but certainly a very crucial system. “It's almost impossible to shut down conveyor 121 for maintenance. By grouping maintenance activities and planning the required preventive maintenance effectively, you can not only improve the conveyor's availability and reliability, you can guarantee them.”
The pilot project turned out to be a major exercise. Because modifications that had been made in the past (the company dates from the nineteen seventies) had not all been accurately documented. Conveyor 121 was figuratively dissected for analysis during a number of sessions: the framework, the controls, the motors, gearboxes and other parts were all accurately analysed and documented. Peter van Dijk: “That was a sizeable one-off investment, but fortunately Optimizer+ allows that data to be copied to other conveying systems in the future.
Predictive value
The simulations performed by EMO using Optimizer+ indicated that 60 hours of annual maintenance would result in an availability of 99.26% for conveyor 121 during the coming 50 years. That prediction allows Peter van Dijk to justify investments in maintenance to his management. “For us Optimizer+ is not just a useful tool that generates appropriate content for our preventive maintenance programme, it's also an excellent management mechanism for budgeting (Capex/Opex). It details your costs for the next 50 years and you know that you can justify preventive maintenance effectively.” Peter van Dijk is not the only person who is enthusiastic about the results of the pilot project. His colleagues are also firm believers. “This has created strong support for applying the method in other areas. It really does give you confidence in the results of your maintenance.”
The data generated by the pilot project has been exported from Optimizer+ into Infor EAM, the CMMS system (Computerized Maintenance and Management System) used by EMO. This software will generate the future work orders based on the maintenance concept and the actual costs of maintenance will also be registered here. After completion of the pilot project, EMO intends to implement a multiphase plan in order to analyse all of its plant via Optimizer+. EMO has purchased two Optimizer+ licences for this work. Furthermore, EMO has also decided to link Optimizer+ to Infor EAM via an existing interface in order to close the loop in the maintenance (and budgeting) improvement cycle.
