This is a compilation of the most popular posts in 2016. Enjoy!
- Myths about PDCA: Learn why people don’t use correctly this powerful tool: link
- Effective vs. Efficient: Is there really a difference? Why does it matter?: link
- Book summary, “Hoshin Kanri for the Lean Enterprise”: How can you use Hoshin Kanri to do an effective policy deployment? Learn from the experts! link
- Hoshin Kanri and policy deployment: Learn the basics of Hoshin Kanri: link
- 3 signs that people are not on board: Engagement is key for the success of Lean. Do you know how to read people reaction to change? link
- Lean, common sense and apparent contradictions: Why are Lean principles difficult to understand? link
Let’s say it straight forward: multitasking does not exist. We all have sometimes perceived that we were successfully doing 2 different things simultaneously, but it was an illusion: our brain is a serial thinker (learn more here or here).
All the supposed benefits of doing 2 things at the same time are false. Our brain can not shift focus from one task to another immediately: it needs time and effort, which decreases dramatically safety (lower attention), quality (more errors) and delivery (less efficiency and effectiveness). In other words: intellectual work follows similar rules as material work. Mental changeovers exist.
Let’s see an example.
Lean for services (Lean for “information work”) must focus in creating a healthy environment to think properly. It is critical to:
- Avoid interruptions
- Make sure all the needed information is available
- Encourage people to save enough time to focus in one specific task
For more information, I recommend these books
- “A Factory of One” (Daniel Markovitz): Lean principles for your individual work
- “Lean Office and Service simplified” (Drew Locher): Lean principles to design information work.
- the basic time blocks that impact OEE
- typical problems that affect the time blocks
- how to divide time to calculate typical OEE components
- A high “loading” component indicates low demand. The work center is idle most of the time. Unfortunately, there is not much to do from an engineering point of view to improve this number.
- A high “planned downtime” component reveals:
- the need of many scheduled corrective and preventive actions. This is a potential issue if problems are recurrent.
- a high number of projects and updates. This is not necessarily a problem if projects are originated by new products or technologies.
- A high “availability loss” component shows breakdowns, large adjustments, or lack of personnel, materials or systems when they are needed. The equipment definitely needs reliability improvement work, standardization and / or better scheduling to avoid starving the machines.
- A high “performance loss” component proves low speed. Standardization and training are typical good next steps.
- A high “quality loss” component obviously indicates that improvement must focus in getting first time quality, reducing scrap and reprocessing.
This analysis is the most important part of applying OEE to our processes. OEE is a means, not a goal. It must drive action and improve the effectiveness of our operations.
OEE is an industrial standard metric used to track performance and find improvement opportunities (click here to read the OEE part 1 post for an introduction to OEE). OEE is basically a comparison between the Net Operation Time (ideal time needed to do a task) and the Real Operation Time (real time needed to do a task). In other words:
OEE = NOT / ROT
However, OEE is not normally calculated as NOT / ROT, but using the more familiar formula:
OEE = (Loading) x Availability x Throughput x Quality.
Here is a short description of each term:
- (Loading): Scheduled Time (TST) / Calendar Time (TCT). Not always included in the OEE calculation. It is sometimes included as part of the availability component.
- Availability: Running Time (RT) / Scheduled Time (TST)
- Throughput: Total Parts / (Running Time (RT) * Cycle Time)
- Quality: Good parts / Total Parts
- Good parts: How many good parts have been produced
- Available time: How long the equipment has been ready to use
- Cycle time: The maximum possible manufacturing speed
This means that there are only 3 ways to increase equipment efficiency: a) Do more good parts in the same time, b) Use less time to do the same amount of good parts or c) Increase machine speed. The following picture shows why:
The availability component shows effectiveness losses related with equipment downtime. This includes non productive time (e.g. weekends), unscheduled time (e.g. unassigned shifts), planned downtime (e.g. preventive maintenance, training, cleaning, change over and set-ups) and unplanned downtime (e.g. breakdowns)
The throughput component shows effectiveness losses related with low speed. This includes running at a lower-than-the-standard speed (e.g we need to run at low speed due to problems with one of the raw materials), short breakdowns (typically less than 5 minutes) and speed limitations due to regulations or machine specifications.
Does it make sense to use any type of aggregated OEE number? It depends. It is tempting to have a general number that shows how the site is performing, but in many cases an aggregated OEE loses the physical meaning of the metric and, consequently, it loses its primary function: be a metric that finds problems and drives action. In case you decide to use an aggregated OEE, please keep this in mind:
- Never use standard averages with OEE. Use weighted averages based on time instead.
- Always aggregate similar work centers. Never lose the physical meaning of OEE
- Use OEE to show problems and find improvement actions, not to compare sites and make rankings
The aggregated OEE can be calculated this way:
OEE (overall equipment effectiveness) is a key metric to measure process delivery and productivity (for more information about the different types of metrics, click here). The theory is simple: OEE compares “net operation time” with the “real time” to see how well things have gone. Let’s see an example:
The concept of Real Operation Time looks innocent, but it is very tricky. There are uncountable circumstances where some people will think that the process is in operation, while others will believe that it is not. Imagine you are tracking a batch and taking data. You have to decide if the following events should be part of the Real Operation Time (or not) to calculate OEE:
- The machine is running at maximum speed
- The machine is running but producing bad parts
- The machine is running slower than it could
- The machine is stopped (breakdown)
- The machine is stopped (no material)
- The machine is stopped (cleaning)
- The machine is stopped (operators training, meetings)
- The machine is stopped (shift not scheduled)
- The machine is stopped (weekend)
Everybody agrees that situations 1-4 are part of the ROT, but then the discussion begins. Typical questions are “Why should I be penalized if I’m training the operators? Or cleaning the equipment? Or if I decide not to use the equipment?”. These are fair questions. The answer is that there is no answer. Everything depends on what you want to use OEE for.
- Do you want to improve machine downtime? Then ROT = 1+2+3+4
- Do you want to improve scheduling? Then ROT = 1+2+3+4+5+6+7
- Do you want to know if you have to buy extra equipment? Then ROT = 1+2+3+4+5+6+7+8+9
The lesson here is that OEE means nothing without a model. The number itself is meaningless. It is the trend (going up, going down) what matters. Everything depends on the model, and the model depends on your improvement goal. Use OEE calculations to help you understand the process and find the problems you need to solve to improve according to your goal. Don’t you have a goal? Then you don’t need OEE.
A typical OEE model look like this:
It’s your choice to decide how many of the seven blocks (NOT, QL, TL, UD, PD, UT, NPT) are part of your OEE. That is your model. All models are potentially valid; a model is good or bad just depending on how well it is aligned with your goal.
OEE is typically divided in 4 categories: Loading, Availability, Throughput and Quality:
- Loading: Scheduled Time (TST) / Calendar Time (TCT)
- Availability: Running Time (RT) / Scheduled Time (TST)
- Throughput: (Total Parts * Max Cycle Time) / Running Time (RT)
- Quality: Good parts / Total Parts
Many people consider that the “Loading” portion depends only on how you decide to schedule work and has nothing to do with equipment effectiveness. Therefore it is unfair to consider “Loading” as part of the OEE and should not be part of the calculation. To solve this philosophical problem, a new metric called TEEP (Total effective equipment performance) is born:
- OEE = Availability x Throughput x Quality
- TEEP = Loading x Availability x Throughput x Quality
The story of OEE has just begun! Don’t miss more information about OEE calculations, typical errors using OEE and an OEE guide in following posts!
Efficiency and effectiveness are two terms widely used in operational excellence and Lean. They are used indistinctly many times, but their meaning is really different:
Efficiency is doing the thing right. Effectiveness is doing the right thing.
Effectiveness is related with the Critical Quality Attributes of the product: those features and characteristics that your customer expects and is willing to pay for. A process is effective only if it provides what the customer wants. Efficiency is linked to Performance: how work is done and how well are the available resources used.
All combinations of effective/ineffective – efficient/inefficient are possible, even the counter-intuitive “efficient & ineffective” (well, some people think that effective is a prerequisite for efficient. This means that a process not doing the right things – therefore, ineffective – can not be considered efficient. It’s a valid point but I’ll consider effectiveness and efficiency independent from now on). Let’s see an example. Imagine I want a portion of pizza for dinner. Four things can happen:
- The taste and temperature of the pizza is perfect (effective) and I get it very quick (efficient)
- The taste and temperature of the pizza is perfect (effective) but I have to wait too long (inefficient)
- I get a cup of coffee instead of pizza (ineffective) but very quick (efficient)
- I get cold pizza (ineffective) and I have to wait too long (inefficient)
Please note that in this example we are assuming that a quick process is an effective process. This is not necessarily true for several reasons. First, speed can be accomplished assigning excessive resources to do a job. This would lead to high speed but also to high costs, which is absolutely not efficient. Second, speed is often a Critical Quality Attribute, more related with effectiveness than with efficiency. However the “speed = efficiency” assumption is a fair simplification for this example.
Efficiency is important; effectiveness is absolutely critical. Ineffective processes are constantly producing things your customers will not buy: this destroys the company reputation and economy. Always solve effectiveness problems immediately. Then, when you know you are doing the right things, it’s time to start thinking how to improve them.
There is nothing quite so useless, as doing with great efficiency, something that should not be done at all.