The Hidden Savings in Operation Agility, Production OEE, and Project Management

7 min read

Automation projects are long-term investments. Selecting the right components, identifying areas of improvement, and implementing sound project management are all crucial factors to consider.

The previous chapter delved into how Automation Project Managers can lower the total cost of ownership (TCO) by:

  • Choosing energy-efficient solutions or using renewable energy,
  • Designing intuitive UX that reduces Operator’s mental load and learning curve,
  • Collecting and analyzing high-accuracy data to optimize production processes, and
  • Equipping employees with durable, transferable, and in-demand skills with a learning and development program.

In addition to the list above, choosing highly reconfigurable solutions and improving the Overall Equipment Effectiveness (OEE) score are essential aspects to consider. Finally, there are three unique aspects of an automation project that Project Managers should be aware of.

  • Evaluate projects as a business case
  • Form a team and a communication plan
  • Manage changes by managing the scope

By understanding these challenges, conquering them, and working with the right partners, the project team can keep the TCO low and long-term returns high.

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Operation agility

Agility helps to realign production and business quickly

Manufacturing agility is a company’s ability to recalibrate production plans in response to fluctuating market demands or shifting business strategies. Cultivating this capability has never been so important in light of recent global events. In its 2021 Manufacturing Outlook report, Deloitte urges companies to commit to increasing operation agility.

To put this into practice, industry veterans agree that shifting away from one-off customized system solutions can strengthen an automation project’s long-term return. Customized systems may have been favorable in the past, but they lack production agility, and retooling or reconfiguring is often impossible or too costly. Experienced integration engineers warn that customized systems may become obsolete sooner because their intricacy makes it hard to source technical support, rendering them almost impossible to maintain.

Good building blocks strengthen manufacturing agility 

Reconfiguration can be achieved by choosing hardware components or software tools that follow stringent industry standards, such as GigE Vision or OpenCV. Experienced system engineers use a Lego analogy and compare these durable, proven components as building blocks for automation systems. Just like Lego blocks, they can be easily redeployed and reprogrammed to serve new applications. This model also reaps the benefits of a shorter learning curve as the operators are already familiar with the technologies and require minimal retraining. 

Well-designed technologies typically have a higher upfront price, but their long lifespan is the true value that keeps the TCO low and long-term return high. Automation project managers use these criteria to help them evaluate a component provider’s technology competency:

How long has the company been in business for the technology they are offering?
  • The longer and more focused indicates they have a wealth of understanding in this field, making their products robust.
  • Also, pay attention to the company’s product roadmap. Does the company have a healthy line-up of products, or does it only have one strong candidate? A balanced product family that meets different needs reflects the company’s ability to bring technologies to market. Lastly, having industry-leading innovations speaks volumes for their R&D ingenuity as well as industry know-how.  
How long have their customers been using their products?
  • A company that designs products with its customers’ needs in mind form partnerships that adds value to both parties in the long-run.
What is the extent of their product support?
  • Products reach their end of life eventually. When the company stops selling them, do they continue to support them? Industrial components are built to be durable. If the provider does not offer long-term technical support, it could very well mean redesigning the entire system when an unsupported component requires maintenance.  
What other measures have they taken to ensure product quality?
  • Industrial components must work under harsh conditions such as extreme temperatures or outdoors in the rain or sun. Look for components that have been tested to work in temperatures ranging from -20 °C to +50 °C (-4°F to +122°F), guaranteeing a wide range of industrial applications.
  • Project engineers also look for industrial components that offer IP certifications higher than IP54 to protect assets from water and dust ingress.

Finally, reputable components also tend to be well-engineered and can have a very long service life. When a company needs to realign its business strategies, being able to liquidate equipment in used asset markets can create positive cash flow. Kim and Kung’s 2014 research proves that the more widely applicable a component is, the higher its redeployability.

Predictive maintenance

Harnessing the power of OEE to predict production downtime

Manufacturers want to avoid unplanned downtime at all costs. According to a 2021 article by the International Society of Automation (ISA), large industrial companies on average lose 323 production hours annually. Among the different verticals, automotive takes the steepest hit at 1.3 million per hour in lost revenue. To effectively reduce overall unplanned downtime, companies can use the Overall Equipment Effectiveness (OEE) framework to craft preventative or predictive measures from the beginning.

OEE is an industry-wide standard that measures a piece of equipment or a production line’s overall utilization. It uses three quantifiable factors to calculate the OEE value. OEE also lists “Six Big Losses” to indicate areas of improvement. The efficiency number is obtained by multiplying together the rates of the following three critical measures:

Availability × Productivity × Quality = OEE

The numerical values of availability, productivity, and quality are between 0 and 1. A perfect production would therefore entail that it:

  • Has 100% availability meaning the equipment experiences 0% downtime or does not need maintenance,
  • Achieves 100% productivity which equals to the production line running at the fastest speed possible, and
  • Scores 100% in quality, meaning no defects are produced.

While pursuing a perfect score of 100% OEE is desirable, the Six Big Losses listed below are inherently inevitable in manufacturing. A better way to utilize this table, as many Process Improvement experts recommend, is to use the Six Big Losses to define a list of objectives the automation project should accomplish. The goals will help Project Managers evaluate and select the right technology or partner that offers the best solution to meet these criteria. This method is especially applicable to companies planning for brownfield projects.

The 6 Big Losses and their respective goals are as follows:

OEE FactorsClassic Big LossesNew Goals
AvailabilityEquipment failureAims for zero unplanned stops
 Setup and adjustmentsAbility to schedule for planned stops
PerformanceIdling and minor stopsAims for small stops
 Reduced speed of operationAims for slower cycles
QualityProcess defects (scrap, repairs)Aims for zero defects
 Reduced yield (from startup to stable production)Aims to reduce waste created during startup or changeover
This chart is adopted from here and modified based on interviews with industry professionals.

What one of the world’s most advanced industries can teach us

Dimension lumber is by far the most commonly used construction material for homes in North America. Quality control (QC) is crucial as any off-target product can jeopardize a building’s structural integrity. Before vision systems were implemented in the early 2000s, a typical sawmill would have an Inspection worker pick a sample of the finished products and measure their dimensions for final quality control.

In case of a defect, the Planer would be halted for recalibration. However, as the inspection was not performed on all finished products, precious resources could be wasted before a defect was detected. Some sawmills even unknowingly shipped undersized or oversized lumber to their clients. To make matters worse, intermittent stops throughout the day, despite being necessary, amount to a significant performance loss over time. It also disrupts upstream processes, causing more needless idling time.

Knowing where the pain points are and let technology help

The first goal was to increase the quality score by detecting the defects as early in the process as possible. Followed by improving the production line’s availability by scheduling for predictive maintenance.

Without redesigning the final Planer process, a real-time vision system was engineered to monitor the dimensions of each passing board. It would halt the upstream process and alert an operator when an off-sized product is detected. The system has a fast scan rate that exceeds 460 m or 1,500 ft per minute, preventing resources from being wasted. A downstream program collects all data to identify trends and inform the MRO team of optimal maintenance dates.

The vision system significantly improved the Planer’s process with higher availability and quality scores. The Real-time Dimension Monitoring (RDM) system became a widely adopted dimension monitoring solution in the wood industry. RDM taken to other machine centers in the sawmill enables immediate detection of a process shift and target size reduction, ensuring sawmills nationwide produce high-quality lumber at a better profit margin. Finally, predictive maintenance also brought in unexpected benefits, enhancing both workplace safety and reducing resource waste.

Project management

Moving the automation project forward with sound management

A competent project management team is the final entity that brings all aspects of a low TCO project together. It is a task force that brings multiple parties together and works with external resources to achieve project goals. Seasoned Project Managers admit that automation projects pose unique challenges but are optimistic that they can still be successful by having a healthy understanding of these challenges.

  • The inherent complexity of automation projects, as they bring hardware construction and software programming together to solve a pain point. Both the hardware and software engineers have to have a certain mutual understanding for automation systems to work in synergy. 

    Most importantly, though, automation projects are business decisions. Whereas PMI defines a project as “a temporary effort … having a beginning and an end”, an automation project is a decision that can and will impact business operations permanently. Identifying the long-term positive changes an automation system can bring should be the underlying goal of any automation project.
  • Communicate not only within the team but with stakeholders, too. Like all projects, discussion with teammates and dialogues with vendors are integral to a project’s smooth implementation. Moreover, early communication with stakeholders such as line operators, supply chain partners, or even nearby communities can positively impact the Change Management process.
  • Change is the only constant. Experts point out that continuous modifications to system specs or even a changing scope is not uncommon, especially in large-scale projects. Understanding that changes are inevitable can help manage project managers’ expectations. Simultaneously establishing boundaries to prevent scope creep and stay on track can reduce frustration.

In the next chapter, we will be offering a practical guideline on tackling these three challenges in managing automation projects.

  • Evaluate projects as a business case
  • Form a team and a communication plan
  • Manage changes by managing the scope

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About The Author - Terry Hermary

Co-founder of Hermary.

Terry is the customer-facing machine vision expert at Hermary with over 30 years of experience. With a background in electrical engineering, he specializes in developing 3D vision applications with system integrators and machine builders. He is passionate about solving unique automation challenges using 3D vision technologies. Over the past three decades, Terry and his team have established Hermary as the leading innovative 3D machine vision provider, revolutionizing industries from sawmilling to meat processing.


  • Co-founded Hermary Machine Vision in 1991
  • Patent holder of many 3D machine vision inventions