Alignment is important to avoid compounding problems.

Alignment must take into account all three dimensions and operating conditions.  Operating conditions include start up, shut down, thermal expansion, gravity, and all other forces.  Equipment moves.  Equipment that is started and stopped frequently is much more likely to experience misalignment.

Institute a program to frequently check for alignment.  The best programs are non-invasive, such as vibration analysis or thermal imaging.  Indications of misalignment that are further down the P-F curve include noise, as well as material degradation.  If you look closely at the photo on the left, you can see some dust to the right of the hub.  This is actually metal that has been worn off.  The shiny portions of the hub indicate that the material is from the hub itself.  The position of the dust on top of the plate is further indication that the material is from the hub and indicates the direction the hub is turning.

Improper equipment operation, intermittent speeds, missed operations, etc are indications of misalignment.  If equipment remains in misaligned or unbalanced condition, it starts to cannibalize itself, like the photo above.  This reduces the useful life of equipment and can even require parts to be swapped out in order to even perform an alignment/realignment.

Misalignment also can increase energy usage.  Although this has been documented at low rates (1-3%), it still affects the overall cost of the operation.

Gravity is thought to effect mostly large, heavy equipment.  Think of the massive shafts that remain spinning to avoid sag.   However gravity can affect smaller equipment if the tolerances are too loose, or if the installation is not in accordance with the engineered properties of the equipment.  Belt drives on the bottom of a piece of equipment, must be engineer for these forces. You cannot turn a normally horizontal belt drive on its side and expect it to perform optimally.  Similarly, I have seen gear drives where the motor is directly above the driving gear.  This puts any unsupported weight of the motor directly on the gear.  When operating, this force is likely negligible.  But starting and stopping the system causes jerk which may loosen supports.  The extra weight can force a misalignment much more easily than a gear that does not have a motor hanging over it.

Even deeper than the drive train, the bearings themselves must be able to handle the forces.  Ball bearings, tapered bearings, needle bearings, babbitt bearings all have their places.  Proper selection of these is key to good alignment.

There are many excellent tools out there to help perform alignments quickly and accurately.  These will even compensate for thermal growth.  However understanding the importance of alignment and the consequences of misalignment make using any tool much better.  Just as in math, don’t learn to add and subtract on a calculator, until you can perform it without one.  Don’t use a tool for alignment until you have performed one the old fashioned way – with dial indicators or even string.  The fundamental understanding from using these simple tools, makes using the advanced tools easier.  The tools don’t perform the alignment.  They give you information to perform the alignment.  People are still making the final decisions, and often the actual adjustments.

Does anyone have an alignment sheet that they find particularly useful?


Overall Equipment Effectiveness (OEE)

OEE definition and formula.

Overall Equipment Effectiveness (OEE) is a measure of how well equipment is able to be utilized.

Why use OEE

  • OEE is used because it is a standardized method of measuring productivity from an equipment standpoint
  • It is an unbiased method
  • By understanding the losses experienced by the equipment we can fix them

How to calculate OEE

OEE = Availability * Performance Rate * Quality Rate

  • Availability = Time available to produce, this is reduced by planned maintenance, change overs, breakdowns, sanitation, and cleaning
  • Performance Rate = The designated speed or rate of production
  • Quality Rate = Good parts produced, or value delivered, this is reduced by defects, holds, scrap, unaccepted work

Data – where to find it; how to use it

  • Availability
    • Usually a manual calculation
    • Most often calculated for full calendar time (24×7; 5×7 – usually operational staffed time) then the unused time (usually market down time) is subtracted from total expected time.
  • Performance Rate
    • Usually calculated from run time information captured on equipment
    • It can be manually calculated but is not practical to manage using manual calcs on large scale operations
    • Theoretical performance rate must be determined and used to calculate the rate
  • Quality Rate
    • Can be calculated on the line if reject system is operational
    • Final calculations may come shifts, days, or even weeks later.  This depends on the quality system and when product is dispositioned from ‘hold’

Common problems to avoid when leveraging OEE for improvement

  1. Not counting all time on the equipment as Available time.
    • Availability can be thought of as an indication of capacity.  If planned downtime (such as that for maintenance, changeover, or sanitation) are removed from the availability calculation, then the load requirements of the equipment cannot be determined.  Therefore changes in production schedule cannot be accurately planned.
    • If 4 hours of planned maintenance is required on equipment each week, that accounts for approximately 3% of Availability.
    • Activities to reduce planned downtime are cannot be value-added if these times are not included in OEE.
      • This is an example of silo thinking.  Engineers working on reducing downtime, either by SMED activities, or instituting more condition monitoring cannot accurately account for the ROI of such activities.
      • In truth, the company will see benefits, but the battle over how the savings are accounted, and who gets to claim the reductions will overshadow the real tangible benefits.  Some will claim the engineers calculations are funny-money; operations will see a real jump in OEE, but not be able to account for the jump.
    • The purpose of OEE is to find losses, and determine if they are worth eliminating.
  2. Using OEE as a measure of people, not equipment.
    • Since equipment is in the very name of the measure, this seems obvious.  But most organizations use the OEE measure to operations, shifts, and sometimes even individuals
    • Management needs to manage.  OEE is best used as a metric to determine where to troubleshoot, but it is never a measure of people’s performance.
    • The purpose of OEE is to find losses, and determine if they are worth eliminating.
  3. Setting a specific number as an OEE goal
    • We love goals, and we love numbers.  Even “Dancing with the Stars” publishes metrics.  However, even the goal there is not to get a perfect score, but to get a better score than last week. – Oh yeah, and a better score than the competitors.
    • I’m often asked what is should a line’s OEE be.  I have spouted “80-85”, but that’s just an arbitrary number.  Who cares what the number is? 80-85% of statistics are made up on the spot (see what I did there?).
    • The purpose of OEE is to find losses, and determine if they are worth eliminating.  That’s it.  Find losses and make a determination if they are worth eliminating.  This means finding a fix for the loss and running an ROI to see if the fix is worth eliminating
  4. Taking action too early or too late to correct
    • The purpose of OEE is to find losses, and determine if they are worth eliminating.
    • Ensure that thorough troubleshooting and root cause analysis are taken on the loss investigation.  Otherwise, you will be solving symptoms, not problems.  This can happen if you react to the data too quickly.  Usually a full week to a month of data are needed to see a good pareto of the losses.
    • Waiting too long to act on the data gives the impression that it is not important.  It takes a lot of conscientious effort by operators to correctly capture and code losses.  If they do not perceive value in their efforts, the downtime coding will become generic.
  5. Not communicating with operators, maintenance, and others how the organization is using OEE and how they are a part of it.
    • Lack of communication will lead to finger pointing and suspicion.  The age old silos of maintenance and operations will use the OEE numbers to blame each other for the recorded losses.
    • Understanding losses is a positive thing.  Do not focus on the OEE number,  instead focus on the losses and how to eliminate them.  You can inspire enthusiasm and spur creative thinking in all team members when root blame is not the focus.

Example Time!pexels-photo-125514.jpeg

OEE Using a Car as an Example

Availability = Time the car is available to drive where you want

  • Reduced by Planned Downtime
    • Time to fuel up
    • Preventive maintenance** (oil changes, tire rotation, tune up, washing, …)
  • Unplanned Downtime
    • Time in shop for maintenance / repairs
    • Accidents
    • Breakdowns
  • Not reduced by
    • Time spent parked

      **Remember spending time on preventive maintenance reduces breakdowns and unplanned downtime

Performance Rate= Time spent with car at speed limit (or expected speed)

Reduced by

  • Idling car
  • Traffic problems / jams
  • Weather related bad road conditions
  • Debris, junk on the road
  • Slowing down in an unfamiliar situation

    Speeding has negative potential consequences, so it is discouraged
  • Tickets
  • Crashes from mis-matched speeds on roads
  • Equipment malfunctions (blown tires)

    Performance rate problems translate into Availability issues

    • Accidents
    • Low fuel economy causing increased fuel stops
    • Breakdowns

Quality Rate: The car performs as expected

Reduced by

  • Low fuel economy
  • Poor emissions
  • Appearance (dirty, paint chipped, rusted,…)  These can become maintenance issues, or interfere with transportation reputation
  • Inability to transport/haul/tow everything you want

So, let’s calculate the OEE for a typical week on a car.

The car is used to go to and from work 5 days per week.  Work is 25 miles from home.  It takes 1 hour to get to work and 1:06 to get home (1.1 hours).

The kids school is 1.5 miles away and the car was driven there 3 times during the week; total of 9 miles.  It took 1 hour for each round trip.

One day during the week there was a stop for fuel and a car wash.  This took 45 minutes.

Standard Performance Rate is 30 miles per hour.   (I declared that.)

There were no quality defects, as all activities performed as expected.

Availability = 100- (Total time car was occupied; 15.25 hrs)/(Maintenance time ; fuel and car wash; .75 hours)*100

Availability = 95%

Performance Rate = 100-(Total Miles/Total Hours Performing) / Standard Performance Rate)*100

Performance Rate = 100- (269/14.5)/30)*100 = 38%

Quality Rate = 100%

OEE =  95%*38%*100% = 36 %

Is 36% OEE good or bad?  The answer is NO – it is neither good or bad.

Areas of losses – potential reductions

  • Maintenance; fuel and car wash – find a faster car wash
  • Waiting for children – determine that OEE is more important and make the kids wait for the car, not the car wait for the kid.  Disclaimer: This is cruel and not to be taken seriously. The point is, this loss is not worth reducing.
  • Perform detailed analysis to improve the Standard Performance rate; make it a variable based on the type of trip.  This is similar to have a performance rate specific to a product.

The car did everything needed, the maintenance was able to be fit into the schedule. The car is not at capacity, therefore it is not value-added to improve the OEE.   So, even though the OEE was 36%, it is acceptable, because the losses were evaluated and the equipment (car) was operating within expectations.  A 36% OEE on a city bus, would likely not be acceptable.  So acceptable is relative to use/application factors.  Use OEE to find losses and determine if they are worth eliminating or reducing.  OEE is a tool, not an end product.



Remote Lubrication Point

Remote Lube Pt Fail_LIRemote lubrication points are a good idea for safety.  They allow for greasing while equipment is running, which is the best way to get grease into the bearing.  However they need to be designed to actually provide the lubrication to the bearing.

The person greasing this has made two mistakes, but the biggest mistake is in the design of this point.


Remote greasing points should be located to minimize the distance the grease must travel.

This design requires the grease to be forced down, then back up the plastic tubing.  Perhaps a better location for the remote zerk would be where I have placed a red dot.  Locating the remote zerk parallel to the actual bearing grease point would minimize the directions that the grease must travel, and also significantly cut the length of the “grease in waiting”.

Relubrication:  The person(s) responsible for lubricating this point need training on observing the equipment.  It is readily apparent that no grease has made it to its destination.  In addition, the mound of grease on the zerk is sloppy.  Some folks like to leave a small dollop of grease on the zerk that is wiped off before the next greasing.  Grease caps are also available to protect the opening of the zerk.  Large glops of grease only make a mess and make in more likely that the wiping off action actually introduces dirt, rather than preventing it.

Competitive Advantage

The simple reality is that maintenance departments are cost centers. Meaning, you cost your company money and do not provide “value add” to the end customer: maintenance does not create salable product, your job exists solely to support salable product.
Maintenance must, therefore, be managed as a competitive advantage. By changing organizational thinking to view maintenance as a competitive advantage, more innovative ideas are implemented. To affect this shift, maintenance is measured by the value produced. First-run output becomes a direct measure of equipment capability, therefore reliability.
Reliability value is measured by the maintenance cost of the best sustainable run output. Sustainable output length is organization dependent; common timeframes include 90 shifts, 3 months, outage to outage, etc.

Reliability Value Example
Best 90 shift output = 9,000 widgets
10 hours/shift yields 10 widgets/hour
Maintenance costs for timeframe = $500,000
Maintenance cost /widget = $55.56

Whenever maintenance costs are below $55.56/widget, the company sustains a competitive advantage. That advantage can be used in profit taking, or in lowering the product price to gain market share.

Maintenance decisions are now based on cost per widget. Consider the decision to enter into Condition Based Monitoring (CBM) at monthly costs of $10,000. To be advantageous, the program must guarantee an additional 180 widgets ($10,000/55.56 dollars/widget). At 10 widgets/hour, the program must improve equipment uptime more than 18 hours/month.

Under cost center thinking, a $10,000/month CBM program would be an unlikely approval. However, when viewed under the competitive advantage model, it can be approved because there is a tangible measure of success – hours of equipment uptime.

cost center graphic

Graphic: Cost / Widget

How have you justified reliability expenditures in your organization?

Failure is not an option … or is it?

Failure is a necessary part of continuous improvement.

How many times have you heard, or even said “Failure is not an option!”  ?

That’s a great movie line, but a dumb way to run in business. If we don’t take risks and try alternatives, there is no progress. Failure is an option, but only if we understand the parameters. Risk taking without a plan, without a mitigation strategy, and without a high probability of known outcomes is not an option.
So how do we option failure? It is simple – use the scientific method. First start with a hypothesis. If x, then y. Next comes the plan to execute x, and finally the mitigation plan if y does not occur. Even if y does occur, it is important to review the whole system and ensure that in the execution of y, other negative consequences did not materialize.
It is easier to look back and identify business failures, but not so easy to identify successes. That’s where metrics come in. Use metrics to measure your successes. Use failures to build your knowledge base. Failure is an option, but make it under controlled circumstances.

I have been involved in many incremental changes, some of them have not worked (been failures), but most of them became the new normal.  All of them provided data and information necessary to make informed decisions.  Speeding up of equipment or lines is a change that almost everyone in manufacturing has been involved in.

  • On single line equipment it is as simple as increasing the speed and holding it for long enough to evaluate the product quality and necessary support actions (refilling packaging, product, or other supplies).  At a certain point, it becomes obvious that the speed gains are off-set by the limit of quality or refilling supplies.
  • On a multiple equipment line, the complexity of finding the optimum running speed can take days, maybe even month.  Often, when by the time the reliability engineer is called in the line is so out of whack (technical term) that it takes significant research to determine what the speeds were, the last time the line ran reliably.  Slowing down a line in these instances is usually the answer to increasing overall equipment effectiveness (OEE).

Steps for implementing continuous improvement (CI):

  1. Start with a stable system.  Results must be repeatable and sustainable to create a baseline.
  2. Determine metrics of the system.  These include not only a metric of the change you want to implement, but whole system metrics to ensure that the change did not cause negative side effects.  This includes how data is captures, the formula for the metrics, and how often the analysis will be performed.
  3. Possible metrics
    • Overall Equipment Effectiveness (OEE)
    • Cost per unit
    • Waste/scrap value
    • Cost of energy
    • Labor usage
  4. Determine the cost / benefit analysis for the change.  This includes the disposition of the product during the experiment.  Is it saleable product, can it be used in rework, are there special disposal costs?
  5. Create a written CI experiment plan.  Try to have as few variables as possible.
    • What is the cost of the experiment
    • What is the expected gain from the experiment
    • How long before the return on investment (ROI) will be realized – assuming the CI project is successful
    • How will the decision for final implementation (new normal or return to base state) be made; including the timing for the decision
      • Is there a plan for early termination should the negative results be clearly evident
      • Clearly define who is responsible for decision making
      • Specify date results will be implemented
    • Clearly state product disposition
  6. Get the CI plan approved by leadership, including funding
  7. Create a written process deviation plan
    1. Post at machinery if possible
    2. Have face to face interaction with each machinery operator to inform them of the plan and their specific duties to the plan
      1. Data collection
        1. What
        2. How often (frequency)
        3. Where (make it easy for the operators to collect/report data)
      2. Tagging of materials
      3. Escalation process (with specific names and contact information) if they need to inform regarding problems/questions encountered
    3. Create clear tagging process (tags, material storage areas) for all material that needs to be quarantined
    4. Start/stop time of deviation
  8. Analyze results quickly and get approval from sponsor for decision
    1. Create an executive summary of the project
    2. Create an implementation plan if new process is to be implemented
  9. Post results to all stakeholders (operators, management, support functions)
    • If CI is the new operating process
      1. Update process documentation, including date process is to become effective
      2. Train all operators on the new process
    • If new process will not be implemented, clearly communicate that to all stakeholders
  10. File all relevant documentation including executive summary
    1. In product folders
    2. In equipment folders
  11. Thank operators for their help
  12. Keep monitoring data, and devising new CI projects

The key to any successful continuous improvement activity is

  • Baseline the current state
  • Determine the changes to be made
  • Allow time for the changes to become the new normal, and then evaluate the data (OEE, or other measure) to decide if you are going to institute the change, or go back to baseline.
  • Make a decision
  • Implement decision
  • Document, document, document
  • Communicate, communicate, communicate

What has been your experience in risk taking?  Did you implement the change, or pull back to original state?  Why?


Organization saves time and money.
You don’t buy things you already have because you know where everything is.
It is easy to find things, and easy to note if something is missing.
The “head down” approach. Just as a surgeon can locate and pick up the right instruments without taking his eyes off the job at hand, our stuff should be organized for ease of use.
Color/shape coding and labeling. Be smart, don’t create visual “noise”
Organization helps find what is “wrong” quickly. Problems are not masked.
Morale improves as working conditions improve.

Manufacturing Excellence

Definition of Excellence; Working to a Common Goal

The goal of the manufacturing excellence program is to build standardization as the foundation for continuous improvement.

The priorities for manufacturing excellence program
1) Build a common operating practice for like machinery and processes. This manufacturing practice must be specific enough to ensure repeatable results in all locations, yet flexible enough to respect differing labor models in each site.
2) Build a continuous improvement model based on data. This must leverage the ERP. Data gathering should truly capture overall equipment effectiveness (OEE). This data can then be used to find the best place to apply resources to improve the manufacturing processes.
3) Drive a model for sharing best practices across the organization. This should include activity based best practice (BP) groups,  business based BP groups, and electronic communication models such as written standards and operating procedures.

What is your definition of Manufacturing Excellence?

How can silos be minimized and everyone work toward the same goal(s)?