Tag Archives: data collection

How Much Can You Trust Your KPIs?

There is more to effective manufacturing analytics than reports. You need an effective and efficient process for collecting data.

By David Oeters, Corporate Communications with CIMx Software

Manufacturing is changing.

3d small people - way choice

Are you using data to optimize production?  Illustration by http://www.colourbox.com

In the past, it was enough to write a few notes on the traveler, type them into a spreadsheet at the end of the day and print up a report. As long as work was completed and product moved, a shop floor could get by.

With the advent of new technology, smart manufacturing, and a digital foundation for production, paper-based data collection is no longer sufficient to support the shop floor. With paper, you can’t easily access the relevant analytics to support process improvement and collaborative manufacturing. There’s no reason not to have relevant and actionable data on production, and a plan to optimize the shop floor.

While reports are important to shop floor optimization, a process to collect the data, relevant data, is equally important. Consider these questions as you review your shop floor analytics program:

  • How is the data being collected?

If you implement a shop floor system to collect and collate data, but still rely on scribbled notes on the traveler or an operator’s memory, then your reporting system is never going to be as effective or efficient as you need.  Transcription errors or missing data may also compromise the accuracy and usefulness.

  • Are you collecting data in all the relevant areas of the process?

Knowing a product has a non-conformance is important for your customer; you also need to know the root cause of the quality escape. Knowing where the non-conformance occurred is a critical step for process improvement. You need to collect data throughout production, not just at completion.

  • Are there holes in the data collection?

Many companies focus their data collection on machines. Pulling data from a machine is easy, but many times non-conformances occur at other points in the manufacturing process. Without data collected at every operation and every critical step, you’re faced with questions on when and how a non-conformance occurred.

  • Quality.

    An MES will not only collect data, but give your data relevance. Illustration by http://www.colourbox.com

    Is the data you are collecting relevant?

Data needs perspective and context to be relevant. An MES provides a framework for manufacturing. The data collected is automatically contextualized with a process, becoming more than a single point in production. It becomes an element in a process.

Giving Production Data Relevance

An MES creates a foundation that both collects the data and gives it relevant perspective. It provides a way to seamlessly, and many times automatically, collect data in real time during the production process.

Data collected is connected to an operation, a production, a work order, and to an operator. You can see the events preceding the data collection and the events following.

If you’re still struggling to peel back the layers in your manufacturing process and understand the root factors in operations, then contact CIMx today for a free shop analysis to see what data an MES can reveal for you.

Improving Quality with Paperless Manufacturing

Manual and paper-based production records are a critical source of errors, and hinder the efforts of quality control.

By David Oeters, Corporate Communications with CIMx Software

Production moves fast.

Assembly lines must keep moving. Machines need to run. Downtime is lost money.

Even in the most exacting complex, discrete manufacturing industry, speed is vital.

With an eye on OEE (Overall Equipment Effectiveness) spending resources and time on anything other than production represents failure.

This might be why some see shop floor data collection as non-value added time – there is no immediate benefit to tracking numbers on a spreadsheet or filling out a paper-based traveler. If your focus is on completing quality work and meeting or exceeding quotas, then data isn’t important.

Be honest – are the minutes saved by “guesstimating” and fudging a few data points worth it?

Confidence Button Shows Assurance Belief And Boldness

Are you confident in your shop floor data and quality control? Illustration by www,colourbox.com

Quality and Paperless Manufacturing

Automated production records and tolerance checks are critically important for shop floor improvement.

An initiative and a few more moments in the morning huddle aren’t going to deliver the benefits of real-time shop floor data. You’ll never see real, sustainable improvement in your records and quality using paper-based records. Asking a Quality professional to do their job with dated records is like asking a dentist to do their work with a hammer.

Manual records have too much margin for error. Trying to design foolproof processes that meet the requirements for audits, give you the data you want and need, and fit your shop floor, is never going to work.

Papers get wrinkled. Notes get smudged. Travelers get misplaced. Humans are fallible.

With even a sliver of doubt, records become suspect and quality suffers.

A modern MES, which automates data collection and production records, ensures the shop floor fulfills requirements through process enforcement.

Then the shop floor can focus on what they do best – production. Quality Control has the tools they need to be effective in their job.

Focus on Manufacturing

Rather than adding complexity and cost to production, paperless manufacturing allows everyone to work better. Improvements become not only possible, but sustainable.

Today, with modern software architecture and the advancement of technology, software is less expensive than ever before.  A system can be up and running and users trained very quickly so you can begin building your ROI within a month.

In addition to automated records and improved quality, you have revision-controlled planning, paperless operations, enhanced planning, and real-time shop floor visibility and control.

Want to learn more, or see how paperless manufacturing can improve your shop floor? The CIMx free shop floor analysis is an excellent way to kick off a new project.

5 Keys to Effective Shop Floor Data Collection

Want to Increase quality, improve production and increase profitability? An effective shop floor data collection will do all this and more, and is much easier to implement than you think.

By David Oeters, Corporate Communications with CIMx Software

How effective is your shop floor data collection? Illustration by www.colourbox.com

How effective is your shop floor data collection? Illustration by http://www.colourbox.com

How important is quality to manufacturing? According to a recent study, it may be the most critical factor in manufacturing profitability. A 1% to 2% increase in productivity may represent more product, but a 1% to 2% increase in quality represents less waste, less scrap, more product, more productivity, more efficiency, and happier customers.

Data collection provides the foundation for quality improvement in manufacturing, and every manufacturer has a quality team or processes in place, yet many companies never realize the full benefit of quality improvement due to ineffective data collection. They struggle to turn the data they collect into real benefit or measurable improvement. In fact, many times inefficient data collection will lead to errors, additional scrap and waste, as well as lost production.

Take a moment to evaluate your current plan for data collection using the follow criteria to identify areas for potential improvement:

  • How “smart” is your data collection?

A smart data collection program is proactive. By catching and eliminating errors early, you can minimize waste and save money and production. A “dumb” data collection delays review of the data, or may not have a plan in place to take corrective action. Looking at a report of mistakes a month after they happened highlights a month of lost opportunity for improvement, and leaves the cause of errors in place.

  • Does your data collection include automatic tolerance checks?

Automating as much of the data collection and check-off process as possible removes potential sources of errors and keeps shop floor employees and the quality team focused on critical tasks. For example, automating tolerance checks will identify quality escapes the minute data is collected. Comparing collected data against the engineering specs is best left to the software system.

  • Does your system eliminate potential input errors?

The truth is, your data is only as good as the system used to collect it. How many times do you input the data? Any more than once is a sign of wasted effort and increased errors. How long do you wait to input the data? What is your source for the data? If you wait till the end of a shop floor shift, when data is collected from handwritten notes on the traveler, then you have a problem. The data you are using is unreliable, out-of-date, and is costing you money. Look for ways to streamline and improve the reliability of your data collection and input.

  • Do you have access to real-time reports?

With modern manufacturing tools and advances in software and technology, there is no reason why the shop floor shouldn’t have access to real-time reports. Today, you can implement a low-cost and low-risk paperless manufacturing system in less than a month, and have a dashboard with real-time shop floor visibility and quality control soon after. With an automated system, you can also move the people who once assembled reports onto more important tasks.

  • How are you using the data that’s collected?

Consider when you are collecting data. Many times a company will collect data once all the work is done. Unfortunately, this data is collected too late to take corrective action. It’s true, this data can be used in an audit or to eliminate a defective product, but both the work and materials are wasted, and planning and shop floor scheduling is unreliable as product is pulled after production. Consider when you can best utilize the data, and when it should be taken. Look at the reasons why you aren’t getting the data you need when you need it. Taking a few moments to collect shop floor data during production is time well spent.


The goal for all manufacturers should be continuous improvement toward optimal production given the machines, equipment and processes being used.  The single most important requirement to achieve that goal is continuous monitoring of shop floor results.  Collection of result data that is automatically verified against specifications and available to decision makers who are tracking progress of all work orders across the shop floor is the best way to continually monitor production and achieve continuous improvement. Give CIMx a call today or leave us a message and ask for a free review of your shop floor processes and a plan to optimize production flow.

Putting secrets of baseball to work on your shop floor!

There are baseball lessons that will improve manufacturing production, increase efficiency, and deliver real-time shop floor visibility and control.

Baseball is a tradition in Cincinnati (the home of CIMx).  Every spring, little league baseball teams appear in every open field, and residents sport at least one (and probably more) piece of Cincinnati Reds apparel.  The city is awash in a sea of red and white for every home game. Excitement for the game is infectious.

What can baseball teach you about your shop floor? Or mobile manufacturing? Or quality? The answer will surprise you.

What can baseball teach you about your shop floor? Or mobile manufacturing? Or quality? The answer will surprise you.

So I leapt at a recent invitation to a game.  A few friends offered me an extra ticket.  It was a great game!  The home team won, I got beer and a hot dog.  But, I didn’t know it was a “working” game.  It turns out one of my friends was a baseball statistician, and we were there to help with a project.

While I watched the game for a wicked curveball, a nice defensive play, or a massive home run, my friend was thinking about probability, applied statistical methods, quantitative analysis and variance theory.  During the game, each of us had a notebook filled with lines and data collection notes.  My job was to collect data on each pitch.  It was hard work!  I had scribbled notes in the margins, question marks all over the page.  Ever try to see the difference between a slider or a split finger fastball from the second tier of a stadium?

And when we were done, sitting at the bar over wings, collating the data was a huge headache.  A key data point was lost under mustard.  Another page of data was missing, likely victim of an overzealous stadium attendant.  My statistician friend was not amused at my unscientific “guess-timates.” After 3 hours of collating, we left without a clear mathematical picture of the game.  All we had was a messy collection of data points that inspired little confidence.

Which, unfortunately, reminds me of shop floor data collection and as-built records for many manufacturers.

I’ll admit my friend set-up what seemed like a “can’t-miss, error-free” system for collecting data.  I just had to mark the sheet for each pitch, log the number for each batter and pitcher, and keep track of when and where in the game we were.  Sounds simple, right?  It was, until reality hit.  We had pitching changes and substitute batters (change orders), bathroom breaks (user-errors), missing and torn notebooks (paper-errors), unreadable data (shop-errors), unreadable notes (input-errors).  All five of us at the game are college-graduates with successful careers, but I was amazed at the number of errors we ran into during the course of a single game.  It was the perfect example of the challenges facing shop floor data collection.

What opportunities for improvement are you letting slip by?

What opportunities for improvement are you letting slip by?

The cost in effort, manpower, and money to create an accurate as-built with paper records is a losing proposition.  Quality?  Unless you have a strong data collection system, then quality production analysis is going to be a “guess-stimate.” Want to use real-time data to track orders or improve production? Can’t do it when your data sits getting dusty in the margins of your as-built book or work order traveler until someone types it into your database. Can you really say your data is secure cruising around the shop floor?  Looking at Lean Manufacturing or Six-Sigma production improvement?  Paper data collection will not get your team where it needs to be. How long does it take you to answer a production question when a customer calls?  Is that acceptable?

So how does baseball keep such accurate records and data?  They have a team of statisticians collecting data throughout the game and a digital system collecting data and identifying errors, which are quickly corrected when needed. Data is kept in a secure location (so stadium attendants can’t clean it away).  The system is designed to automatically create usable records (real-time reporting) from the data so baseball junkies can get their fill of real time baseball stats at the click of a button.

Sounds nice, doesn’t it?

We have accurate baseball records going back decades.  This is data we can trust (as long as you ignore potential “juicing” in your analysis).  Want to know how the Cincinnati Reds did in 1982? The data is there, accessible at a push of a button, and it is trustworthy.  Not that you would want that data, because it happens to be one of the worst seasons for the Reds (first time they finished in last place since 1937).

How far can you go with the right tools and processes in place? Photo credit www.colourbox.com

How far can you go with the right tools and processes in place? Photo credit http://www.colourbox.com

Your shop floor can and should work like that.  Data collection should be a seamless part of the process for real time data collection, just like the team of data junkies that pore over and analyze every baseball game. Ensure accurate data with built-in safeguards.  Improve quality with a system that compares work plans with current data, flagging non-conformances. Production improvement is possible only with accurate and efficient data collection.  What could you do with anywhere, anytime access to real production data?  If the baseball brainiacs can access the pitch count from a random game five years ago, why can’t your shop floor produce accurate as-builts when it comes time for an audit?

The truth is, they can.  It is not difficult to implement shop floor data collection.  A controlled, phased implementation is a low-risk process that ensures an ROI for each phase, and will improve production, reduce errors, ensure quality, and create accurate real-time records that for an easy, timely, and efficient audit.

So, my first effort at baseball stadium data collection was a failure (but did get me a free baseball game, beer, a hot dog, and wings… so it wasn’t THAT much of a failure).  But, we learned a lesson.  Next time, we’re going with tablets and an app (our own version of mobile manufacturing). A laptop is collecting data and correlating it for real time accuracy. We set up a process one evening, tested it during a game on TV, and it’s ready to be implemented at the next game.

What kind of shop floor data collection system do you have?  How do you use and control your production data?  How quickly can you prepare for an audit?  If you’d like to know more about how you can improve your manufacturing process and shop floor data collection, contact us today. We’re happy to help.