BOOSTING PRODUCTION WITH SIMULATIONS
FSP has adopted a computer-assisted simulation program, which can be used to detect the strengths and bottlenecks of production processes without disturbing the actual production.
The simulation program, Tecnomatix, is supplied by Ideal PLM. The program has been commissioned, for example, at the FSP surface treatment plant in Kangasniemi, Finland, where it was the key in finding a solution that will double the production volumes.
To put it simply, the idea is to create a realistic model of the production process, and then test the options received as a result of the modelling process. Consequently, it is possible to choose the best alternatives, i.e., optimise the production.
Getting rid of ‘gut feelings’
“We started running simulations with our partner, Ideal PLM, in early 2017, and we have executed simulations in Poland and in two Finnish facilities, in Raisio and Kangasniemi. Production processes contain an immense number of variables and multiplier effects that simply cannot be counted ‘with pen and paper’. In essence, the best part of using a simulation program is the fact that decisions aimed at process improvement can then be based on mathematical data instead of ‘gut feeling’,” says FSP’s Development Manager Juli-Ann Rikkonen.
The Kangasniemi surface treatment plant is a long-term partner of its neighbour, Tehomet Oy. Head of Unit Lauri Leppänen had made assessments implying that adding another powder coating oven to the production line might double the production volume. The simulation corroborated this assessment, which provided the Tehomet investment planning team with support for making further decisions.
“The simulation also verified that adding another oven would not cause multiplier effects which would require extending the facilities or recruiting more staff members. In fact, Kangasniemi is now able to lift its operational capacity to a level that is ideal, both for the customers’ needs and the working pace of the surface treatment workers,” Rikkonen says.
According to Tehomet Production Manager Tomi Pasanen, the simulation and the related analyses support the plans to invest in a new oven. The final decision is made and schedules drafted later in 2018.
Tehomet is part of the American Valmont Industries group, and it is the Nordic countries’ largest manufacturer of custom steel and wooden lighting poles, brackets and high masts.
Valuable tool for boosting customer’s production
Rikkonen is in charge of simulations and the related implementations at FSP. Work distribution between FSP and Ideal dictates that FSP defines a problem and determines the objectives, and consequently gathers initial data from production. The data then goes to Ideal PLM for modelling, simulation runs, analysis and result documentation.
The arrangement works well, because the collection of initial data – e.g. work phases of a product in production, work phase specific processing times for products, personnel numbers and capacity – require the skills of the local management, as well as the reports they collect from production.
“How much time it takes to simulate a production facility’s operation depends on the production volumes, operated lines, and the number of different products in production. In addition, the requested level of simulation accuracy affects the duration. It is not even reasonable to strive for 100 % accuracy, because observing all the possible and even unlikely variables would take too much time in relation to the gained benefit. The normal accuracy is approximately 90–95 per cent, but often we do get close to 100 per cent,” says Mikko Vehviläinen, Business Development Manager at Ideal PLM.
Rikkonen is very happy with the co-operation with Ideal PLM. The abbreviation PLM comes from the words Product Lifecycle Management.
“FSP now has a customised simulation program which offers us an even more reliable tool for showing our customers different ways to develop their production.”
Production is mathematics
“Using simulations saves both time and money. The production facility’s performance is improved, production bottlenecks are removed, and the facilities and machinery can be operated with full capacity,” Vehviläinen lists.
In addition, the security of production planning is improved, and the total sum of investments can be reduced by 5–20 per cent.
“The simulation executed in Kangasniemi showed that adding a new powder coating oven to the production line would increase product lead times up to 60 pieces per hour, which is 50 per cent more than currently.”
Did the Kangasniemi simulation provide any surprising results?
“Actually, a simulation should never result in any total surprises. The purpose of a simulation is to confirm an assessment into authenticated data that can be used to calculate the factors that are promoting or hindering production,” points out Vehviläinen.
At the moment, the most labour-consuming simulation phase is the collection of initial data, which is carried out by utilising e.g. different accounting and calculation programs. “Even this has not been a problem. In fact, the work distribution is ideal: we collected the initial data that might be difficult for outsiders to grasp, and the simulation was then executed quickly by professionals,” Rikkonen adds.
The entire simulation process in Kangasniemi took only a few days.
“It is completely possible to use different identifiers, data collection methods and programs to identify and monitor the pieces in production. In such case, the phase times are automatically entered into a specific program, and the data can then be accessed without manual monitoring. Then again, the automatisation of data collection is usually more profitable in larger production facilities than Kangasniemi,” sums up Vehviläinen.