AXXOS OEE is a software solution with a strong focus on production monitoring and optimization. The application works well standalone in all different manufacturing industry areas. AXXOS OEE is also a top of the line shop floor component that smoothly integrates into MES solutions.
AXXOS OEE gives you access to detailed information so that you can identify the sources of losses and potential improvements in production. Overall Equipment Effectiveness (OEE) is a key performance indicator that describes how efficiently machines are operating, and helps to locate any bottlenecks. OEE measurement provides the foundations for setting up targets and measuring the results of daily improvement activities.
– We already knew that some of our machines had stoppages, but not why. With the help of AXXOS OEE we have reduced downtime by just over 50%, Jens Krisat, Quality Manager at Seco Tools.
AXXOS OEE is a tool for day-to-day production monitoring that can help your company improve continuously. It makes gathering and presenting information quick, easy and convenient. AXXOS OEE lets you check critical information, such as machine availability, OEE value per machine, part or order, and the most common causes of stoppages. The system gives you a solid basis for decisions that shows in black and white what action you need to take and where. AXXOS OEE rapidly alerts you about problems, efficiently documents losses and lets you quickly analyze causes and effects. The time you save gives you more opportunities for active improvement.
OEE (Overall Equipment Effectiveness) is a globally accepted standard for measuring manufacturing productivity. In short terms – it identifies share of the total manufacturing time that is truly productive. An OEE value of 100% means you are manufacturing only good parts, as fast as possible, with no stop time. The OEE value of 100% means 100% Quality (only good parts), 100% Performance (as fast as possible), and 100% Availability (no stop time.
Availability (A), is a measurement of how much of the planned production time the machines really are in operation. Unplanned downtime, such as tool change, staff shortages, lack of materials, machine failure, etc. are losses that affect the availability.
Equipment failures and disruption as well as setup and adjustments together make up the machine downtime losses, this is described in the section of the Six Big Losses below.
Performance (P), also known as speed loss, shows the loss of each machine. Loss such as reduced production rate, incorrectly set speed, not tuned machine or deliberately chosen a lower rate because of quality issues and the like, affecting performance.
Even loss where the machine is not running at maximum speed and has been further reduced in speed generate performance loss.
There are several methods to determine the maximum performance rate, it may well be a value from the machine manufacturer, or the theoretically fastest possible speed, or the highest rate ever achieved in production.
Idling and minor stops, together with reduced speed on machine’s performance, this is described in the section of the Six Big Losses.
Quality Yield, (Q), shows how many of the produced units that can be sold at full price. The losses are divided up into two categories: those of pure scrap that have no value at all, and those who that does not have top quality can, but can still be sold at a reduced price.
The difference between the units that can be sold at full price and those that sell at a reduced price can be seen as a loss and should be mapped out. Defects in the process and reduced yield reflects the machine’s quality losses. This is described in the section of the Six Big Losses.
Most companies have been ineffective in visualizing and resolving less visible losses, such as shorter stops and speed loss. A ”short stop” is short, but frequent stops, which are difficult to identify, and therefore sometimes seen as a part of the production flow. There is often a big unused potential with these short stops, by resolving these recurring stops your OEE numbers will increase.
Speed loss means that the machine does not manufacture products at the rate that it is designed for. More about these losses can read about below.
Any downtime that occurs in the machine is covered in this category. When stops like these occur losses such as lower production volumes and increased process time will develop. The cause of machine disturbances and interruptions can be both temporary and recurring in nature.
Temporary disturbances are commonly known as breakdown and can for example mean that the control system or central components of the machine breaks down and needs to be repaired or replaced. These events often mean that the machine must be stationary for a long time. Recurring disturbances may include problems with the software, or that the pressure suddenly falls in the lubrication system. This means that the machine must be temporarily turned off. To reduce these losses, it is important to break the problem down into small pieces, especially when it comes to recurring problems.
When coding stop causes manually in logbooks, you usually only record the larger obvious stops. This leads to that the smaller, recurrent disturbances being left out without a permanent solution.
Set-up time and adjustments cause loss of production and at the same time is often the cause for defective products being manufactured before the change and adjustment has taken place.
Set-up time is the time it takes to prepare the machine from producing one product to another. You may have also have to do some adjustments after the set time, and in some cases it takes time for adjustments beyond the actual change. To reduce losses, it is important to take into account the disturbance of different parts; the mechanical adjustment and alignment of the machine separately.
The loss during short stops occur for example when a product is caught in a feeding machine or debris get stuck or get in the way. The problems are easily solved but the time loss may be significant in the long run if it occurs often, and if the errors are not noticed by the operator quickly enough.
The difference between these short stops and chronic disruptions is that the short stops do not depend on the machine itself, but the material or other equipment. However, they are equally difficult to detect and analyze because the operator usually does not record these small disturbances. Idling losses means that the machine is not operating even though could, due to lack of material.
The loss arise in that the machine runs at a slower speed than it is designed for. It can be difficult to see with the naked eye and therefore a loss that is rarely perceived as a loss, because the machine actually still produces articles.
It is extra difficult to discover the loss if the machine produces multiple types of articles, where there is a large variation of the target cycle time for each article. In these cases it is particularly important with a Product Monitoring System that can handle the stop times on order and article level.
This definition covers losses like scrap and lost production. Defects can arise, for example due to incorrect processing, which might be due to temporary and intermittent interference.
When a part has to be discarded it is not only the raw material that is a loss, but also the wasted production time.
The parts that can be revised should also be considered a loss. Partly because they take up time for the operator, but mainly because of the machine time used for a value-adding process.
This is a quality loss that arise while starting up a machine that is unstable which lead to a number of faulty articles being produced before the process becomes stable.
Such loss occurs mainly after a new set up, or if the machine has been turned off.
Follow up on your stop times, stop causes, downtime, scrap and other key performance indicators in production. It’s hard to improve and streamline unless you continually measure your production. To measure is to know!
In order to effectively improve your OEE value it requires that you know your current situation. By installing a system that automatically records the OEE value in your production it will tell in black and white how well your production is optimized. AXXOS OEE is a Production Monitoring System that simplifies the operators’ work. Forget all the handwritten logbooks and Excel files. It is easy, quick and reliable to collect OEE data from the machines with AXXOS OEE.
AXXOS OEE automatically collects data about down times and cycle times.
Enter the downtime cause types and scrap causes, register items and orders on / off.
Present of OEE-value, MTBF, MTTR, downtimes, etc.
Visualize your production status in real time with AXXOS Visualize.
Drill-down and analyze your manufacturing data quick and easy with AXXOS Analyze and use your time on value-adding improvement work.
AXXOS OEE smoothly integrates with surrounding business- and manufacturing systems, to eliminate the need for re-entry of data and to get full control over your production data.
Get easy access to information for your improvement process and for decision-making in reports, factory overview and AXXOS Analyze.
AXXOS Analyze is a powerful and easy-
to-use tool for analysis of production information. With a few clicks you can scrutinize everything from the overall information for the whole of production to detailed information at department, machine, order or part level.
AXXOS Visualize gives you the production status in real time. Follow the current situation on large displays in the factory, at workstations or from mobile clients. Increased awareness will let you focus more on productivity and improvement activities.
AXXOS OEE continuously gathers data directly from the machines. Operators and supervisors can report the reasons for any disturbance and thus build a database that reveals how the well the production is running and why. Data is easily collected from the machines with PLCs or OPC connections.
Automatic gathering of production data and one-click reporting frees up time to let the operators focus on improvement. Clear visualization and solid data for decision making lays the foundation for effective and well planned improvement activities.
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