oee.cloud is a system for Overall Equipment Effectiveness (OEE) analysis in manufacturing processes. The system can be used independently or as a flexible supplement for a potentially existing operational data collection (ODC) system. With oee.cloud, the OEE and its loss causes can be recorded without any intrusion into the system control, without IT effort and without investment, and in detail – with the help of artificial intelligence – to be analyzed. Typical users are operation managers, master craftsmen, CIP / improvement teams, industrial engineers or maintenance staff who want to understand and optimize the causes of equipment productivity loss.
The Advantages of oee.cloud at a Glance
Modern Industry 4.0 OEE Management for production processes quickly installed and for rent:
- Installation in 30 minutes at each equipment
- Stand-alone hardware; no interference with the system control (= PLC), also usable for systems without control or sensor technology (= retrofit); no thread for the data security of the equipment, no need for an IT project
- Sensor transmits data to oee.cloud independently via mobile network, wireless lan, or LAN; Data transmission always possible
- Encrypted access to all data via a web browser, storage of data in the German cloud; no installation of software necessary
- Modern graphic data visualization, all data also for download
- Loss reason entry via inexpensive consumer tablets; no investment in expensive input devices
- Identification of productivity increase potentials through artificial intelligence and machine learning without the need of a data scientist
- Amazon Alexa voice interface to all OEE data (currently only in German)
- Use for short-term or long-term rental; no investment needs
- Availability in 6 languages, more to be added if needed
Straightforward Sensor Hardware
Generally, either the oee.cloud sensor hardware or a unit count signal from the equipment control can be used. Many customers prefer the oee.cloud sensor hardware, as it allows for minimally invasive deployment without intervention in the equipment control and without connecting the system to the Internet.
In order to automatically capture an important part of the OEE calculation data without any intervention in the system control, oee.cloud provides a hardware consisting of the IoT gateway and a sensor head to be selected.
The IoT gateway only needs to be connected to a 110/220 volt power supply and will be shipped in an IP 69 rated enclosure to meet sanitary requirements for steam jet cleaning.
Data transfer from the equipment to the oee.cloud can be done in 3 ways:
- via mobile data: installed is a multi-SIM, which automatically searches the strongest available mobile network – all over the world
- via wireless LAN: if a wireless LAN coverage is guaranteed at the equipment location and from there access to the Internet is available
- via LAN: if a LAN socket is available at the equipment site and from there access to the Internet is available
To the IoT gateway, via standard industrial connections, a standard sensor head of e.g. Sick or Pepperl + Fuchs is connected. Commonly used are light sensors, inductive or capacitive sensor heads to determine the current quantity and speed of the equipment.
The use of the oee.cloud hardware is not mandatory. If the data can be transferred in a different way to the oee.cloud, e.g. a data transmission via a TCP / IP-capable PLC, is also possible.
The received data are processed graphically in the oee.cloud and made available in an Internet browser after a secure log-in. The user has the possibility to select, analyze, and display the data according to various criteria, such as e.g. shifts.
In the upper area, the data is selected to days and shifts or times. Below, the three OEE factors – availability, performance, quality – of the selected days are visualized in a bar chart. The solid black line indicates the OEE for each day.
Below are two so-called “heartbeats”. The lower line determines the zoom – visible through the blue colored area. This time period will be detailed above.
In the upper heartbeat line the number of units is visible in minute resolution. The red solid line visualizes the current default speed, the bright red areas indicate loss of availability, with the loss reason displayed with a mouse-over as additional information.
For the respective selection all important key figures of the equipment run are evaluated. It shows the OEE in its components as well as KPIs such as meantime between failures, meantime to repair, and the no-touch time between micro-stoppages.
The next step is to analyze the causes of the losses. For this purpose further detailed analyzes are available.
The availability losses are analyzed in terms of number, duration and a percentage distribution. In the waterfall diagram, the loss reason and their distribution are visualized. In this way, it can be analyzed in detail, which losses with which causes and at what time were present.
The same methodology is used to evaluate the reasons for the loss of performance, which usually receives little attention in day-to-day business. oee.cloud also captures them and makes them transparent.
Simple Loss Reason Entry
With the input of the loss reasons oee.cloud sets on humans. Only he can decide in the complexity of the entire system, what is the actual cause for a standstill was. That’s why we made it as easy as possible for the employee to make these entries. Commercially available Android or iOS tablets have been proven to detect the causes of availability, performance and quality losses.
The tablets also require internet access and are usually attached to a workbench or shelf with a gooseneck. If an input is required, the tablet receives a push notification and displays the loss catalog, whereby different catalogs can be configured for availability, performance and quality losses.
Company-specific loss reasons can be entered at a maximum of 9 levels, so that individual loss detection per sensor location is possible, and the employee only has to make a few clicks on the display to classify a loss. After how many minutes of equipment standstill or reduced equipment speed a prompt appears on the display is configurable. The prompt is supported both visually and acoustically to attract the attention of the employees.
The tablets can either be self-procured or rented via oee.cloud.
Andon boards visualize the current status of the production. oee.cloud displays live the status of the equipment, the current shift OEE and the course of the equipment performance for the respective shift. This information can be visualized on any display with web access. Displays without a built-in browser can e.g. inexpensively and easily to be upgraded with a Raspberry Zero. This means that all relevant information can be displayed in important locations such as the shop floor directly at the equipment, in the meeting room or in the office. The presentation of one to a maximum of eight equipments on a large display has proved its worth. Of course, the display can also be used on any laptop or tablet.
OEE-Analyse mit künstlicher Intelligenz
Anomalies are hidden in the OEE data stream: After some set-up procedures, the system quickly returns to the crest line, while it takes longer to do so in other conversions. Some products produce more micro-stoppages than others. Whether an installation should rather be run faster – or slower and thus with fewer micro-stoppages – can be calculated: These analyzes are usually not performed as of today. However, manufacturing according to Industry 4.0 principles does just that – capturing data, intelligently evaluating it on a large scale and presenting it on-line to people for decision-making.
oee.cloud provides an anomaly cockpit for the analyzes. OEE data is prepared for analysis in the cloud database and AI algorithms analyze it in real-time so that anomalies – and productivity losses – can be detected as they occur.
It is important to know that no data scientist is necessary for AI use. All configuration and training tasks of the algorithms and the neural networks are performed in the background after a period of data collection by the expert team of oee.cloud.
More information on artificial intelligence can be found here.
Voice Interface with Amazon Alexa
For humans, language is the simplest interface to other people and in the future also to “things”. oee.cloud has therefore developed an Alexa skill for querying the OEE data. This skill works on both the Amazon speakers and the Alexa apps, which you can install on both iOS and Android devices. In this way, Alexa answers a large number of questions about the OEE of your equipment.
A sample video in German with English subtitles can be seen here.
More information about Alexa can be found here.
Realtime Shopfloor Workflows with Industrial Smart Watches
Industrial smart watches move into the factories. Employees wear a sturdy Smart Watch on their wrist and receive information from the systems in this way. In this way it can be ensured that e.g. in multi-machine operation, even in hectic phases, no activities are lost. oee.cloud establishes the direct connection to the systems without them having to fulfill a technical condition. So the employee gets informed when a system comes to a standstill or whether it runs slower than expected. It is also possible to enter loss reasons via the Industrial Smart. Events start one workflow each, which can also be passed on from employee to employee. This is how fast and efficient communication on the shopfloor of the future looks like.
You can find more information about smartwatch deployment here.
Flexible Use and Licensing
oee.cloud is available in the cloud from a digital data center in Germany. Thus, German or European data protection law is applied. If required, all operating and safety certificates can be viewed.
The data transmission is encrypted via the Internet. The use is billed on the basis of connected equipments for a rental period starting from one month. If a contract is concluded for several systems and/or a contract period of one year or more, the user charges are discounted. The amount is a flat rate for all users of a business, including usage, data transfer, maintenance and updates.
Increase Equipment Productivity through OEE Management
The two founders of oee.cloud, Prof. Dr. Markus Focke and Jörn Steinbeck, wrote a book in Springer Verlag in 2018 titled “Increasing Equipment Productivity through OEE Management” which is available in German.
The book describes the basics of OEE as well as the steps to a professional digital implementation. The book can be obtained via Amazon.