Those operating manufacturing plants face a real challenge. How can they best evaluate the ability of their equipment to perform well at the lowest overall cost? Many vendors offer potential solutions. These can be summed up as methods to digitize data to make it more useable, ways to gather more data, or systems that analyze mountains of data to transform it into actionable information.
But it is far from being only a technological problem. Focus solely on the implementation of technology or the deployment of the latest IoT, machine learning, or artificial intelligence (AI) engines fails to solve underlying issues. What data should be gathered? What data should be given priority when it comes to analysis? How can the results of analysis be harnessed for the benefit of the organization? After all, more data than ever before is available; capturing, analyzing, and displaying the right data in the best way can be an elusive goal.
A metric devised to bring order to this confusion is Overall Equipment Effectiveness (OEE). Widely used in industry to measure the performance of equipment, it is made up of three main components: Availability, Productivity, and Quality.
Let’s take a look at each of these:
Availability measures how much time the equipment is available to run production. All non-production activities such as maintenance or engineering upgrades negatively impact this measurement. The simplest way to measure it is to look at the available time a production machine could be running and minus the amount of time it is not running regardless of the reason. For example, if a machine should be running for eight hours during a shift and it is only running for 6, it would be graded at 75% availability.
Productivity addresses the level of performance. How many parts are produced per unit of time. If 100 units can be produced per hour and only 80 are produced, then the activity scores 80%.
Quality is the ratio of good versus bad products. If 100 units are produced, but only 90 pass inspection, the OEE rating for quality is 90%.
Many companies use OEE to monitor production. If they achieve 100% on each of the three, they score an OEE of 100%. However, an overly simplistic view of availability can lead to poor management decisions.
Ideally, a machine should be operating at an optimum level all day. The reasons why this may not be the case can vary. It may be due to a missing operator, a lack of maintenance staff, delays in the performance of routine maintenance actions, a power cut, etc. If management sees availability drop, it may incorrectly demand that the production manager motivate his staff to work harder. But management may be solving the wrong problem due to a lack of comprehensive data. Do they need more operators, an additional maintenance person, or some other solution?
Siemens has worked out a way to more accurately assess actual conditions. It is predicated on machine accountability utilizing a brand new RFID switch.
Siemens RFID Switch
Earlier methods of determining who did what and when on the shop floor were crude at best. Anyone could use a traditional key switch or hand it over to someone else. Passwords, too, suffered similar frailties. Paper logs to record when a machine entered into maintenance mode or production mode were often incomplete or left empty for long periods. So how can we do better?
The RFID Key Switch from Siemens is a 22 mm pilot device which communicates to any PLC or DCS via an open technology called IO-Link. These read-only keys have a unique shape that provides protection against tampering or duplication. They can easily be attached to a key ring. Operators that run multiple machines at one time can be assigned multiple keys. The supervisor can quickly assign new keys as needed. Lost keys can be identified if they are ever used again.
Every key is a read only device. A unique hex code ID assigned at the factory. This is similar to a MAC ID for Ethernet-based products. When it is inserted into the machine, the PLC matches the ID code from the RFID key to previously stored values to identify its owner. By tying the key into the Siemens Automation system, you know who is doing what and when with the system. The PLC records date, time and action every time a key is inserted or removed.
The operator inserts the RFID key into the machine at the start of the shift. If maintenance is required, he or she removes the key and requests assistance. When maintenance arrives, they insert their own RFID key and begin. That key is removed when their work is finished. This system enables management to view a more accurate picture of machine status. Instead of jumping to wrong conclusions, they have enough data to make informed decisions.
It is recommended that RFID keys be set up to transmit and store data to Siemens controls and automation systems. As stated earlier, more data than ever before is available; capturing, analyzing, and displaying the right data in the best way can be an elusive goal. Siemens offers two solutions for analyzing and displaying this data. The first is by using Siemens WinCC Performance Monitor for analysis. Recorded data can be turned into useful information which can then be displayed on dashboards using WinCC HMI software. The second solution is a Siemens Cloud based solution called MindSphere. The recorded data is stored in a secure Cloud based server and the analysis and displaying of the data is accomplished through the use of Apps.
By doing so, OEE information can be viewed and intelligently assessed. Mean Time Between Failures (MTBF) data on machines and equipment can be collected to note potential maintenance or supplier quality concerns. Additionally, Mean Repair Time and further Key Performance Indicators (KPI) can be tracked, analyzed, and displayed by Siemens WinCC. This aids management in finding the right cause for production slowdowns and in finding ways to streamline manufacturing operations.Have an Inquiry for Siemens about this article? Click Here >>