6 mistakes manufacturers are still making but can’t afford to

Hard Hat - Ball Engineer M
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Challenges for discrete manufacturers were always relatively tough, but in recent years they have become nearly impossible to manage.

This year, it has never been more important for companies to be agile, with the seismic impact of the COVID-19 pandemic, as well as a general global landscape of increasing competition, decreasing margins and increased market demand, all combined to create a landscape that even the biggest players struggle to adapt to fast enough.

A manufacturing CFO survey revealed that the top two business priorities for manufacturing CFOs are investing in technology or infrastructure (26%) and cutting costs (17%). This is set against a backdrop of 38% of CFOs reporting their business was struggling and 35% that they were surviving, while just 25% claimed to be thriving. It is likely to be the most innovative companies that invest in optimization technology to cut their costs which thrive in the new now. With margins remaining relatively low and the risk of making mistakes getting increasingly higher, even when it comes to the most experienced and recognized manufacturing brands, the need to avoid common and painful pitfalls increases. This is where Industry 4.0 and cloud-based technology is uniquely placed to help, as ROI becomes more important than ever.

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Following over a decade of close collaboration with top discrete manufacturing players, we’ve come to know and learn some of the most widespread mistakes.

The following issues exist “across the board”, meaning that they exist in every region and sector of the discrete manufacturing industry. Keep reading to learn what they are and how to avoid them.

Mistake #1: Failing to plan a crisis exit strategy

This is not a new one, but it has been thrown into the spotlight by COVID-19. It is the discrete manufacturing businesses that have planned their way out of the pandemic which – like all crises, will eventually come to an end – who are most likely to thrive in the new now. For example, why not take advantage of the time available to improve your resource utilization and address issues so that you are using your resources as efficiently as possible and can scale up or diversify your work methods as needed?

Emerging from the huge disruption of the past 12 months will involve careful planning and forecasting as the future will look very different. The temporary setbacks that currently exist will make way for permanent changes, particularly in discrete manufacturing industries such as aerospace, automotive and heavy machinery. As a crisis ends, businesses emerge into an environment that will inevitably have permanently changed from the pre-crisis world. In such uncertain times, implementing cost-saving strategies in areas you can control, such as waste reduction and process automation, are a key part of overall resilience.

Technology and automation will be central to many companies’ exit strategies, providing them with the necessary agility and enabling them to stay competitive. Now is a great time to implement digital transformation and cloud solutions, which can be deployed remotely, streamlining operations and providing real-time data that allows for rapidly changing production demands.

Having an exit plan can apply to any crisis that envelops a business, so don’t delay getting a plan in place for how to emerge from major setbacks and global challenges, because it is resilient manufacturers – those which have digitization tools in place and end-to-end crisis management strategies – that will be most successful.

Mistake #2: Unoptimized OEE 

The importance of optimizing  the Overall Equipment Effectiveness (OEE) is well known to manufacturers. In fact, if you ask anyone that has been in the business long enough, they’ll probably tell you that they are always focused on optimization, and that they have been successful so far.

Unfortunately, chances are that they’re wrong about that, and, in truth, what most manufacturing managers consider to be an optimized OEE can usually in reality reach far better results.

OEE greatly affects a manufacturing businesses bottom line and can make or break profitability. Done right, it delivers streamlined manufacturing, with full oversight of where all assets are located on your production floor. However, failing to measure it properly may create problems, such as the false impression of a maximized machinery availability level. The first step involves calculating a correct link between OEE and profitability and an accurate measuring system. That’s not easy to do, I am quite aware, since measuring OEE and its influence on ROI in real-time is a challenge, but it’s important, nonetheless.

Some manufacturers have learned to create a clear and visible OEE metric that is based on the quality of work, the level of performance and the availability rate of their equipment. Factors such as the cost of owning redundant tools or putting too many safety margins in place, for instance, must play a part in this calculation as well. When everything is taken into account, the picture becomes vividly clear and the areas that require optimization are easier to detect.

Industrial IoT technologies and optimization solutions can help you calculate your real OEE and significantly optimize it.


Mistake #3: Poorly maintained tools 

Do you know exactly where each tool your production floor relies on is currently placed and why? Can you tell how many high-temperature hours this tool has already absorbed since its last maintenance cycle? Do you keep track of tools that are about to wear out, and require critical maintenance?

If you’re anything like many known discrete manufacturers out there, chances are that the answer to both questions – as well as other tool-related ones – is not always.

And that is a problem. Lost, outdated, unmaintained tools result in delays and reduced quality products that lead to rework and cost manufacturers a fortune.

Though the industry is well aware of the need to reduce scrap and rework costs, and indeed numbers are decreasing (largely due to the adoption of Industry 4.0 technologies), studies still report an average rework and scrap cost of roughly 8% of sales.  

We’ve long discussed the importance of machine and tool predictive maintenance and the message remains just as simple: real optimization isn’t just solving maintenance issues as they arise, it’s knowing which tool is about to demand some attention and handling it before it creates workflow issues. If you’re not one step ahead, you are lagging behind.

Mistake #4: Using insufficient or outdated technological solutions 

It may be strange to hear in the 20’s (and it sure is strange to write), but in the age of Industry 4.0 solutions, complex manufacturers are still using manual procedures, manual repetitive activities, and manual decision making. 

It is easy to understand the challenge around catching up with technology, as indeed, things are changing rapidly… 

Not long ago, manufacturers moved to digitalize their factories and simple ERP software solutions took over. But, today, things have changed so dramatically, and AI-based IIoT optimization solutions offer manufacturers a huge advantage over their competitors.  No simple ERP or any other data analysis system can beat AI-based actionable insights, in real-time. 

Imagine this: Manufacturer X enjoys automated real-time alerts such as: “this tool was misplaced”, “that station can’t be used for this task as it will provoke a missing deadline incident”, “this tool needs to go to maintenance now or there’s a rework risk” or “please use this material with this serial number. It’s located here. As it faces the higher risk of being expired, better use this first”. 

In contrast, all along, manufacturer Y uses outdated software solutions and hence runs manual calculations and reaches insights alone. At a certain production scale, there is no way manufacturer Y can remain competitive. 

Some manufacturers are intimidated by adding more software to the blend, while others are more traditional at heart or don’t fully understand the ROI of industry 4.0 technology solutions

Either way, the result is that this mistake may play into the hands of the competition.

Mistake #5: Missing out on today’s automation 

A more specific mistake involves choosing manual labor over automated procedures. 

Manufacturers that opt for manual data feeding are losing 4 times: once, when they have to work that much harder to manually feed their systems with data; twice, when it takes them far longer to complete the task; a third time, when they reach the wrong result due to human errors and the fourth, when the data isn’t changing processes, in real-time, as it should. 

“humans are the least reliable components in the manufacturing system” 

Well, no surprise here. Us humans may not like to hear this, but a study conducted by the U.S. military and aerospace programs finds that we are the least reliable component in the complex manufacturing system. If even highly trained and disciplined US military personnel make 20% more errors, one can only imagine what the gap is when it comes to the average worker. 

It’s hard to blame humans, as doing this repetitive work for hours on end is bound to result in less motivated employees. In contract, cloud-based solutions deliver both real-time data and improvements in human-machine interaction.

Mistake #6: Confusing old school methods with AI-based optimization

As mentioned before, AI rose to fame so fast that many of us haven’t quite figured out what it practically means for manufacturers (and, if you think understanding AI is hard, wait till you read about Quantum technology). 

This has led to some confusion that is leveraged by some industry players. I’ve seen multiple simple manufacturing management solutions vendors add the buzz term ‘AI’ to their title, despite the fact that they lack the unparalleled capabilities and competitive edge that a true AI-based solution offers. 


While humans will always make mistakes, some mistakes are greater than others. Out of many mistakes that I keep being exposed to, I’ve shared 6 that are both very common and very risky, in terms of manufacturing profitability. 

Since all of these mistakes can be solved, as shown in this article, and since some sophisticated industry players have already worked these challenges out, and provided us all with best practices, I truly believe that being aware of these mistakes is a good start. 

By preparing for the new future as well as the new now, avoiding making these 6 key mistakes and optimizing their operations, companies can ensure they thrive and stay well ahead of the competition.

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