What is TEEP (Total Equipment Effective Performance)?
My security guard is willing to guard my house 24hours a day, but I tell him to guard my house for only 12 hours. OEE measures how effectively he is doing the job in 12 hours. TEEP, whereas, measures the same, and in addition, also measures the extent of my stupidity in stating him to work only 12 hours a day while he was willing to work for 24 hours straight.
Losses on the shop floor can be classified as Equipment losses and Schedule losses. Loss occurred when the machine is scheduled to run are called as Equipment loss. We can measured it by OEE.
Schedule losses are concerned to the period when the machine was not scheduled to run but was still available to do so. For example, Lunch and tea breaks, non-working shifts, holidays, and no orders. This is measured as Utilization.
OEE vs. TEEP
- TEEP considers both equipment and schedule losses, i.e. OEE & Utilization
- OEE measures how efficiently you spent your scheduled production time
- TEEP measures how efficiently you utilized the entire calendar time
- Utilization = Planned Production Time divided by Total Available Calendar Time
- TEEP = OEE and Utilization multiplied
A machine’s OEE is 70 %. It runs 24 hours a day without a break, 5 days a week.
The Utilization is 5/7, or 71.42 %.
TEEP = 100 x ((OEE/100) x (Utilization/100)) = 50 %
A machine’s OEE is 60 %.
It works 12 hours a day, with lunch and tea breaks totaling 1.5 hour, 6 days a week, the Utilization is (10.5 x 6)/(24 x 7) = 37.5 %
TEEP = 100 x ((OEE/100) x (Utilization/100)) = 22.5 %
If I take out a bank loan to purchase a machine, the bankers expect to be paid the principle + interest on the loan every month. They don’t care how long I operate the machine. If I only run the machine for 12 hours a day, my revenue is half of what it might be if I operated it 24 hours a day. If orders are not a limitation, it makes sense for me to operate my machine for longer periods of time — 24 hours, across breaks, and so on. TEEP makes more sense as a measure of my capacity to repay the bank loan than OEE. The TEEP definition, TEEP computation and OEE vs. TEEP differences are therefore important to understand.
The term Industry 4.0 standard is meaningless. There is no specific designed criteria by which you can claim, “This system complies with the Industry 4.0 standard.” Industry 4.0 is simply a term for a type of automation defined by the collection, transfer, and analysis of data via sensors connected to machines, the internet, and the cloud.
However, Industry 4.0 is based on a set of design principles:
Interoperability: A system’s or component’s ability to work well with other systems or components.
Information transparency: The ability to collect and process machinery activity using electronic sensors for other uses.
Technical assistance: First, the ability to assist people by reporting and informing them so that they can make decisions. Second, the ability to assist people by completing unpleasant, tedious, or dangerous jobs.
Decentralized decisions: The ability to decide and execute tasks as autonomously as feasible. Decisions and duties are only delegated to humans when they become particularly complex or have conflicting objectives.
The extent to which each of these principles are implemented can vary, and will likely rise as technology advances in the next years.
There are several standards for the various components of Industry 4.0 like sensors, cloud, IoT, etc. and how they are work like protocols, securities, etc. but there are no specific standard that states “This is Industry 4.0 and this is not”. If there is any system that follows the design principles listed above, that is Industry 4.0
230 years ago, in Industry 1.0 there were no specific standards revolving around the number of machines run on steam and steam used. Similar to that, seen today, there is no set rigid conformance to Industry 4.0 standards.
Machine tools will soon be referred as cyber physical systems (CPS). CPS regularly pops up in the IIoT discussions. CPS can be defined as an architecture where embedded and networked computers monitor and control the physical processes with a feedback loop.
Flexible machining environment where machine tools are equipped with in-process measurement and closed-looping structures are helpful for IIoT integration. Compressed air lines, hydraulic systems, chip conveyors can all be part of this integration marathon.
One of the crucial application that requires cyber physical systems is the energy management in factories. It requires to monitor and manage the power consumption by each device, machine and other equipment. This development can optimize the energy consumption and balance the speed. This way machine operations that are energy intensive can be scheduled during the day when utility rates are minimum.
Currently, the important and useful concept regarding cyber physical systems is control loop. Industrial IoT can help to implement the control loops from device level to the enterprise level in factories.
A monitoring software is an application that talks to numerous devices and provides real-time dashboard to the industries which is notification and reports driven to improve the productivity and prediction ability and is one of the integral part of IIoT
Machine shops are now stepping in to utilize the strength of Industrial IoT. Most of them are installing the monitoring system. This is the recommended approach as machine monitoring can introduce the main elements required for IIoT connections. Basic machine monitoring requires equipping machines, establishing the framework for data collection and network configurations, training supervisors and managers to deal and recognize the data management issues, and the list goes on.
Most of the shops that implement monitoring system tend to implement these in modules, with a small number of machines so as to ease the learning experience. The real-time networked system implement machine-to-machine communicational platform.
Organizations involve managers and co-workers in deploying this machine monitoring system so as to encourage them to provide valuable input and also receive clear and simple directions to implement and use them on the regular basis. This would also help the rigid workers to understand that this system is too to help them and not hinder their current state of work.
This typical part also involves installing the large display screens for showing reports for machine utilization. This visualization creates a strong impact to analyze the results faster and rationally.
Once this monitoring system is installed and works as expected, the shopkeeper can further deploy additional sensors to customize the dashboard and reports to achieve additional targets.
Cloud computing and Big Data are no more in the shell. Everyone has read about it at some or the place. These two elements or rather, technologies, are at the core level of Industrial IoT. The concept behind cloud computing is a computer processor placed at remote location runs a specific application or software rather than running it on each user’s computer. User can interact with the system via a network on the cloud. Most of the times this network is Internet.
Since the storage and processing capacity of the cloud is unlimited, it provides more economic, convenient and secure storage alternatives. The growing storage capacity can also be met as the cloud is expandable.
In connected IIoT, data is expected to flow to and from the connected devices. These streams of data usually get larger with time and that is when Big Data comes in existence. Integration of Big Data into Industrial IoT can help to generate, access and gather the huge amount of data.
For example, a specific CAM programming algorithm is more efficient at removing the most material with least amount of energy. In such cases, programmers can be notified regarding this option when cloud-based programming resources are enabled.
Industrial Internet of Things (IIoT) has a dramatic impact on the industries just as social media has on any teenager of today, probably, even more. Teenagers do get tired and need some rest. But machines are expected to run continuously and perform optimally as long as we maintain them.
Over the years, maintenance has been reinvented. Whether it was reactive, predictive or time-based, every maintenance policy that you use conceives the mindset of your working managers. They sure are loyal to their companies and proud of the methods they use but are largely reluctant to change the same.
Imagine possessing a monitoring system that’s always on, generating automatic repair recommendations and is smart enough to auto-populate work order system. Such systems may also reduce unplanned maintenance and spending on capital equipment by 90%. All these is possible in today’s age by the means of sharing machine data and following the initial repair alerts that such gateways detect.
The idea of replacing process with automation, and experience with smart system may seem impractical to novice entrepreneurs but implementation and applications of IIoT are proving them all wrong. Information is extracted and consumed by every little thing around you.
You may not implement such systems now, but someone else is already using it or will be using soon. They are looking for ways to improve machine efficiency, exploit vulnerabilities and receive what they expect from the machines. Efficiency application of technology and Internet plays a very vital role in such strategies. And the first ones to implement these, wins by huge margin as there are no second chances in the industry. The second prize winners are kind of fishermen who drive where the fish were day before yesterday.
With Internet available everywhere and data moving to and forth every second, how can you afford to not use such amazing condition monitoring systems that provides valuable insights, at by itself!