- HIDRIA Dieseltec
- Company Location: Tolmin, Slovenia
- Approx. 300 employees
- Production of complex assembly lines (engineered to order by HIDRIA Technology Center)
- Production of pressure sensor glowplugs and general glowplugs (mass production)
The FACTS4WORKERS solution at HIDRIA Dieseltec
Context of use
- Manufacturing of glowplugs
- Complex automatic assembly lines
- Event-driven maintenance
- Process monitoring
- Complex and automated production lines with lots of fault conditions
- Solution finding highly dependent on the experience of the operator
- Event based intervention if parts are suddenly out of specification or the machine stops on other reasons
Room for improvement
- Improve the knowledge management regarding problem solving and problem prevention
- Use the production data to analyze and predict upcoming fault conditions in order to prevent them
- Upskill the operator to be able to do more maintenance work by himself and to help him preventing machine stops
- Less machine stops due to preventive maintenance and by changing from an event based intervention schema to a more planned one
- Faster problem solving due to aggregated and available problem solving support directly supplied by the machine
The FACTS4WORKERS solution
@ HIDRIA Dieseltec
@ HIDRIA Dieseltec
The Facts4workers solution provides the workers with all relevant information for the setup of the production line, manufacturing and the maintenance processes.
Field of applicaton
Benefit of the FACTS4WORKERS solution
Field of application
- Manufacturing of mass production components
- Maintenance of the production and assembly lines
- Shared information among workers
Defect and Solutions
The solution provide access to a repository of solutions for most of the production issues that arise during production. The developed system is directly connected to the PLC of the production line to obtain a clear and timely classification of the problem and suggest the optimal solution to the workers. Solutions are created using a bottom-up approach: the workers introduce the solutions in the system to support each other efforts and create a collaborative environment. The rating of the solutions and the possibility to add documentation (video, photos, text) to an existing solution enables the development of a continuously evolving solution environment that could support the workers.
Process monitoring will allow the workers to have a continuous feedback about the status of the process and enable them to take improvement actions as soon as a negative trend is detected. The process monitoring is based on the direct connection of the F4W solution to the measuring devices and process parameters logging solutions on the assembly line. This approach is able to “connect” the workers to the machines and enhance their consciousness about the process.
The access to shared documents on the spot will allows the workers to gain in autonomy and reduce their stress about missing information. The documents available in the on-line repository will include manuals, quality control sheets and all the required info to maintain a single component of the assembly line.
HID – Support for complex tasks
When Mihail comes to work, he first prints out the (maintenance) checklist to check the production for the coming week. This is how the operators ensure the machines are running smoothly, as they get instructions on what needs to be checked on each machine. Then he calls a morning meeting with the operators to go through everyone’s tasks. Checking operations includes a lot of manual documentation and correcting mistakes (updating various things) in the current IT system.
Right after the morning coffee break, a machine in the assembly line triggers a warning that something must be checked immediately. Mihail knows how to fix the machine, as he has worked on all the lines in his past and gained a lot of working experience. The information he needs in this repair situation is in his head. One operator in the team attempts to fix the problem directly by replacing a defective pneumatic actuator. When it is finished after half an hour’s work, Mihail writes down the replaced part in the machine book. In the case of larger or more complex problems, the internal maintenance team helps to bring the production back to speed again as quickly as possible. Sometimes Mihail needs to call the product technologist or an electrician for help. Product technologist knows the machine the best and is responsible for the quality of the pieces being made.
In the afternoon, as per the production plan, it is time to prepare the assembly line to make another product (part). This requires very accurate work phases, and many things need to be checked before the machines are adjusted and calibrated so that the new products will be produced according to their specifications. Besides the switching tasks, machines sometimes require accurate special adjustments when there are deviations in incoming components. “We have to set the production according to these deviations in this component” (Mihail).
After a day filled with many different tasks, even though they were completed successfully, Mihail once again considers how the worn-out machines could be replaced with new ones. They would be more reliable and also have a lower noise level than the current ones. Although it takes time to learn how to use them, they would be better for everyone in the end.
As his first task for the day, Mihail checks all the recent production events with his new F4W tool. He and his operator team each use their own F4W tools to get the automatically updated instructions on what needs to be checked on each machine for the coming week in the assembly line. Those on the operator team allocate tasks for themselves to check. Each operator documents all the activities performed on each machine in the new F4W solution. It is easy to update machine information and correct mistakes. Mihail is happy to get rid of all the manual paper work and to have all the information about the machines in his new electronic machine book.
Right after the morning coffee break, a machine in the assembly line triggers a warning that something must be checked immediately. In his new electronic machine book, Mihail checks the early warning indicator, which was the cause of the warning, and how to fix the problem. In this case, the fault was indicated to be a defective pneumatic actuator, as the sensor in actuator triggered a warning that it is over the limits of the acceptable measurement value. An operator in the team replaced it directly. When it was completed, within 10 minutes, the operator Mihail writes down the details of the replaced part in the new electronic machine book. In the case of larger or more complex problems, the line operator team first documents its knowledge in the new F4W solution, which helps Robert to make a proposal as to how the problem could be solved. The solution is based on the knowledge of line operators and on a proactive process fault analysis about real-time machine-run data by applying machine learning and big-data analytics or analysing product quality trends and deviations. Robert and his maintenance team also help to bring the production up to speed again as quickly as possible based on this information.
In the afternoon, as per the production plan, it is time to switch another product on the assembly line. Mihail and his line operators are preparing for the switch task by utilising a new smart ‘hand-held’ F4W tool in addition to the special gauges and devices. The procedure of switching to a new product requires data to be put into the machine, as well as product information (pulled from specifications, tolerances, drawings) and knowledge of the whole assembly workflow. Product information is in the i4 software system that Mihail uses five to six times per shift for different checks.
After a day filled with many different (successfully completed) tasks, Mihail can now share his knowledge of the assembly line through the F4W solution to train other workers. He feels that it is really good to have manageable data and information helping man and machine, and he is now a knowledge worker.
HID – Event driven mainteinance and shared information
When Robert first arrives at the workplace in the morning, he checks whether anything has gone wrong with the machines. He walks around the production area and checks whether there are any service orders. After a couple of minutes, the production leader brings him a service order. There has been a major breakdown in one of the machines, and it has been stopped, so Robert gets the request to fix it. He goes to the machine and talks to the line operator, who tries to find a solution to the problem and seeks information in his machine book, but without any success. Then Robert makes a phone call to the product technologist, who is responsible for the machine and knows the machine the best.
Robert and the technologist have a meeting to discuss possible solutions to fix the problem. Robert calls the machine manufacturer (Hidria TC) to get more information about the problem and find a possible solution. After the meeting, a solution is found based on information from the manufacturer and a common understanding with the line operator and the technologist. After the meeting, Robert uses his laptop (using the Hidria-wide system for ordering spare parts) to order the special parts from the machine manufacturer and receive them in the shortest possible time. On the service order, he also makes a note of some of the information that can be used in the future.
Robert gives the service order papers to his team’s maintenance worker. Robert knows that when he sees a paper on the table, there is still work to do. The maintenance worker performs the necessary maintenance actions with the machine and also writes down on this document all the hours spent and the spare parts used. When the work is finished and the machine is running, the document is given back to the technologist, who is responsible for documenting the case in the electronic LN software system (includes e.g. requests, service orders, accounting system). The system gives Robert a cost breakdown of the service orders, including all the bills, hours and materials.
In the afternoon, Robert is preparing a check list and timetables on the machines for preventive maintenance. He has received feedback (event-based intervention schema) from one of the line operators that one of his machines is making an unusual noise. Another line operator has informed him that a sensor of the machine is showing that one of the measured values is outside the permissible limits. Robert decides to prioritise these two maintenance activities at the top of the maintenance check list. He gives the service orders to his team’s maintenance worker and operates the machines himself. After a long day, he feels happy that all the machines are working and the production is in good condition. However, he feels a little nervous about what will happen the next day.
When Robert first arrives at the workplace, he checks where anything has gone wrong with the machines. He checks from his laptop whether there are any service orders for him and his team and is happy that no service orders were generated during the evening or night shifts.
After a couple of hours, Robert gets a message through his F4W tool that an urgent new service order has arrived. At the time, he was in the coffee room, so he leaves immediately to get more information about the breakdown from the new F4W solution. He discovers that the specific machine has been stopped and requires immediate action from his team. The line operator has just documented his grasp of the problem in the F4W solution without any success in solving the problem himself. Robert goes through the machine data. The F4W solution has detailed information about the machine, when and where it was purchased, the recorded tolerance deviations of past production runs and carried out maintenance activities. In addition, Robert goes through all the notes in the system that the line operators have made concerning this specific problem.
The new F4W solution helps to predict certain errors based on an analysis of the machine data in the system. Robert discusses the solution approach with the technologist, and they agree on the actions to be taken regarding the machine. In the F4W solution, he also documents some information about the problem and the solution they found, which will help the line operators or the maintenance team to resolve similar problems in the future.
Robert assigns one of his team members the task of fixing the problem. The maintenance worker gets the message to the F4W tool that a new service order has arrived, and he checks the assignment from the F4W solution. The maintenance worker takes the necessary actions with the machine, and in the system he documents how many hours were spent and some information about the spare parts. In the F4W solution, the maintenance worker also makes a few notes about the special tasks or things that have to be taken into account when fixing the problem in similar situations in the future.
In the afternoon, Robert is preparing a check list and timetables on the machines for preventive maintenance. He analyses the production and machine data in the F4W solution to predict upcoming maintenance work. The F4W solution gets the data that one of the sensors of the machine is near the limit of the acceptable measurement value. Robert adds the task to the timetable in order to react to this problem during the week.
After a long day, Robert is happy that all the machines are working and the production is in good condition. He likes that his work time has been reduced significantly in relation to reactive maintenance tasks. The line operators are able to predict and solve most of the minor problems in the production line with the help of the new F4W solution. Therefore, Robert can concentrate more on the preventive maintenance and development projects. He really likes analysing the machine and production data from the new F4W solution and thus preventing many potential breakdowns.
Improvement with regard to influencing factors.