Harnessing Artificial Intelligence for Manufacturing Performance Improvement

Artificial Intelligence (AI)—once a concept boxed within the realm of science fiction and futuristic fantasies—has become a reality that is continuously reshaping various industries. One such field feeling the significant impact is manufacturing. This blog explores how businesses can harness AI to improve manufacturing performance, from refining product quality to enhancing operational efficiency.

Understanding AI in Manufacturing

Artificial intelligence, in a nutshell, refers to computer systems designed to mimic human intelligence, including aspects like learning, reasoning, problem-solving, perception, and language. We are primarily focusing on its pivotal role in manufacturing—a sector where machinery and processes are fine-tuned to infer patterns and insights from manufacturing data.

Two crucial techniques form the bedrock of AI’s transformative effect—Machine Learning (ML) and Deep Learning. ML facilitates automatic progress in computer performance via exposure to data, while Deep Learning, a subset of ML, deploys neural networks to analyses multitude facets of a given scenario.

Applications of AI in Manufacturing

AI in manufacturing may feel intangible, but its applications are concrete, quantifiable, and coupled with direct strategic impact. Here are key areas where AI has a discernible influence:

Predictive Maintenance: AI provides the capacity to predict possible machinery malfunction by identifying patterns in data accumulated from the machines. By fixing issues before they halt operations, unplanned downtime is significantly reduced.

Quality Control: From inspecting minute product details to assessing whole batch quality, machine learning algorithms can pinpoint product defects. This early detection system prevents the manufacture of flawed products to save costs and protect brand reputation.

Demand Forecasting: Market trends prediction is an essential aspect of manufacturing, and AI can do it with remarkable accuracy. Advanced data analyses enable producers to realign their production strategies according to the forecasted demand.

Supply Chain Optimisation: AI conducts extensive analysis of multiple supply chain factors, offering manufacturers an intelligence-informed logistical strategy that improves inventory management and distribution patterns.

Automation of Processes: Complex tasks, previously requiring human intervention, can now be done independently, thanks to AI-driven automation tools. This evolution reduces common human errors and improves factory safety.

Benefits of AI in Manufacturing

Increased Efficiency: AI can significantly ramp up efficiency in manufacturing processes on multiple levels. For instance, intelligent machines can analyse historical and real-time data from the production line to identify bottlenecks and make real-time adjustments, leading to more streamlined operations. AI systems can improve the speed and accuracy of routine tasks by automating them. Machine learning algorithms can also optimise resource utilisation, reducing waste, and improving overall effectiveness. Given these enhancements, operations run smoother, faster, and with less waste, thereby dramatically improving efficiency.

Reduced Operational Costs: The use of AI has financially tangible benefits. With predictive maintenance capabilities, AI can analyse patterns in machine data to predict potential malfunctions before they cause expensive downtime. This ability to forecast and act upon potential problems in advance can significantly reduce costs associated with last-minute equipment repairs or replacements. AI can automate many processes, freeing the workforce from routine tasks and reducing labour costs. AI can also help cut the costs associated with overproduction and inventory wastage by providing accurate demand forecasts.

Improved Quality: AI can effectively learn from data to discern anomalies or variations in manufacturing processes that could result in defects. This instant identification allows for speedy correction, minimising the chance of producing defective components or products. Machine vision, powered by AI, can also be used for stringent and objective quality checks, reducing human error, and thus ensuring consistent output quality. The end result is improvements in the final product quality, enhanced customer satisfaction, and a stronger brand reputation in the market.

Enhanced Safety: In the manufacturing industry, employee safety is vital. With AI, potentially hazardous tasks can be automated. For instance, in a high-temperature environment or one that involves handling hazardous materials, robots equipped with AI can execute tasks without risking human safety. Moreover, AI can monitor facilities for safety compliance and detect any potential threats, triggering alarms for immediate action. By taking on jobs that would put humans at risk and by monitoring worksites in real-time for potential safety hazards, AI significantly enhances worker safety.

Challenges and Solutions

Data Privacy: With AI systems increasingly analysing vast amounts of data, privacy concerns are rising. Manufacturers collect operational data, customer data, and more, which if not secured properly, can easily be used maliciously, damaging both customers and businesses. However, AI itself provides a solution in terms of ‘Differential Privacy.’ This technology adds a degree of randomness to data, without affecting the broader analyses. This ensures that individual data entries cannot be reversed-engineered, protected from potential intrusion.

Cost of Implementation: Implementing AI in manufacturing is often seen as a financially intensive approach. It requires considerable upfront investment for acquiring necessary hardware, developing AI models, integrating with existing systems, and training staff. However, a long-view perspective suggests these costs are recoverable given the long-term benefits. Enhanced operational efficiency, improved product quality, reduced downtime, and minimised wastage result in substantial cost savings over time, serving as the return on investment.

Lack of Skills: AI requires a specific set of skills, which if not present in the current workforce can pose learning and implementation challenges. It is essential to impart comprehensive AI training to employees— to introduce AI concepts, demonstrate its application, and make them feel comfortable with AI tools. Additionally, aggressive hiring strategies focusing on attracting AI-skilled workforce can be incorporated. Partnerships with educational institutions for tailored programs or accelerators for AI startups could also be a pathway to gain access to skills and innovative solutions.

Key Takeaway[s]

Harnessing the power of AI promises a bright future for the manufacturing industry. The possibilities are endless, the improvements significant, and the breakthroughs rewarding. It is a realm of opportunities businesses must explore, offsetting challenges with innovative solutions while continuously devising ways to keep up with AI advancements. Whether it’s to respond to market volatility, improve product quality or enhance efficiency, the introduction of AI into manufacturing indeed signifies a significant leap forward.

The Lost Art of Activity Sampling: A Forgotten Tool in Modern Manufacturing

Activity sampling, coupled with time study techniques, has, unfortunately, become a forgotten art within the realm of present-day manufacturing. As was once meticulously drilled into eager minds, everything eventually comes down to time. It is thus essential to scrutinize the best and most efficient utilisation of time for all our undertakings.

While there are myriad tools available, activity sampling stands out as one of those formidable tools to always have in your armory. It’s a phenomenal method that enables economically studying extended activities or a group of such activities, yielding statistically accurate data.


Understanding Activity Sampling?

To delve deeper into the concept of activity sampling, imagine a group of machines, processes, or people observed over an extended period. At regular intervals, the observer records the ongoing activities at random periods of the day/week. Every observation precisely notes what is happening at a given time—eventually building a measure of the percentage of time the activity spans over the hour, day, or any chosen timeline.

This method proves especially useful in estimating the proportion of value-added time to non-value added time within your business processes. Typical observations may cover instances such as machine breakdowns, transportation of material, change-overs, periods of waiting, operating, and paperwork filling, etc. Although these examples tilt more towards manufacturing operations, the method is equally vital in examining back-office processes and identifying potential time-consuming activities to boost personal productivity.


An Example Activity Sampling in Action

Let’s take a practical example to understand these observations. Consider sampling the activity of ‘packing’ involving three people/processes. The activity is conducted over two hours at random times of the day/week, with observations taken every two minutes. The results can be illustrated visually to represent allocated percentages for each task.



This analysis provides an opportunity to identify possible improvements to work smarter (and not necessarily harder). The process can be augmented by a spaghetti diagram to emphasise material and person movements, detailed time study work, and process mapping.

When analysing, one may notice that Packing Process 2 showcases no computer time within the two hours. Upon further inquiry and understanding, one realizes that Packing Process 2 batches their paperwork before processing it in one hit. Activity sampling would help identify this difference wherein the observation percentage compared to the other two processes would have been higher.

The Benefits of Activity Sampling

Activity sampling presents numerous advantages. It offers unbiased results and can be paused at any point without compromising the results. It’s a technique that can be mastered even with limited training. It allows teamwork to be studied and compared. Given its economical nature, it’s also less time-consuming than many other traditional time-study techniques.

A Final Word

Today’s competitive and fast-paced world demands sharp insights and efficiency across the board. The lost art of activity sampling, if recovered and embraced, can play a critical part in maintaining competitiveness and driving consistent improvements in productivity for businesses in any industry.

So, the question beckons. Are we ready to rediscover this lost art to maximise our potential and fulfil our quest for increased productivity and efficiency?

Productivity – SMEs Making Slow Progress

UK Productivity and the SME focus

I do find it interesting in reading reports on UK Productivity and the SME focus on how there are a lot of SMEs making slow progress in this arena.

If we step back, which some reports have eluded to… the SME government funded programmes have always been based on growth and employment opportunities (NOT Productivity) so is it any wonder we have some issues. Growth and employment is an excellent focus and most SMEs want more, albeit it does bring its own set of issues and problems.

Additionally in reviewing the Growth and Employment Objective, I also question some of the programmes themselves. When I see that surveys have been completed across their customer base and the customer has highlighted they want Strategy and Tactical Planning, Continuous Improvement, but have been sold Website upgrades, Public Relations, etc. (again though this is aligned to the programme output of growth and employment??? Wrong objective, wrong KPI perhaps???)

Have we shot ourselves in the foot with the focus on Growth and Employment? In some respects, possibly, but we can do something about it? If we accept that’s it’s a problem of course.

Do we need to focus internally? Absolutely, if you want to drive productivity this is where the focus needs to be. (regardless of whether its operations, sales, back office)


Growth is far easier with operations that generate predictable and repeatable results. If they are not stable (least waste way of working) we will now exacerbate the effect on our already poor operational processes and performance (ie: Productivity)

Productivity is only one of the key KPI’s within a business, along with On Time Delivery, Quality, Cash, Profit, etc.. each may have a gap that needs to be worked on.

Each KPI (key performance indicator) needs to be monitored, managed and actioned.

The equation y=f(x) is one I always remember

Y: the outcome or outcomes, result or results, that you want

X: the inputs, factors or whatever is necessary to get the outcome (there can be more than one possible x)

F: the function or process that will take the inputs and make them into the desired outcome

Change the X and you change the Y (limit the variation in X we limit the variation in Y)

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Leveraging Growth Mindset and Fact-Based Management in Manufacturing

The difference between stagnation and growth often lies in mindset and management approach. The case of an SME Manufacturer with an £8m turnover, which lost a monumental £1.5 million order to a competitor that did not even manufacture but merely outsourced, illustrates a vital lesson in resilience, mindset, and strategic focus.

The Importance of Managing by Facts

Today’s manufacturing landscape demands a shift from traditional, often emotionally-driven decision-making to a more robust, evidence-based approach known as ‘managing by fact.’ This paradigm underscores the necessity of grounding decisions in data, metrics, and factual evidence rather than intuition, gut feelings, or emotions. It’s a shift that aims to heighten efficiency, enhance productivity, and foster innovation by making informed decisions that are aligned with strategic objectives and market demands.

Understanding ‘Manage by Fact’

‘Manage by Fact’ is not just a catchphrase; it’s a comprehensive approach that encompasses:

  • Data-Driven Decision Making: Leveraging real-time data and analytics to guide strategic decisions, leading to more targeted and effective outcomes.
  • Performance Metrics: Establishing clear, measurable objectives that help in assessing performance against goals, thereby facilitating continuous improvement.
  • Objective Analysis: Encouraging a culture where decisions are made based on objective analysis rather than subjective opinion or hierarchical pressures.
growth mindset

The Power of a Growth Mindset

At the heart of the SME Manufacturer’s story is the concept of a ‘growth mindset,’ a term coined by psychologist Carol Dweck. It denotes an underlying belief that talents can be developed through hard work, effective strategies, and input from others as opposed to a ‘fixed mindset’ which posits that talents and abilities are static and unchangeable.

A growth mindset in manufacturing signifies:

  • Embracing Challenges: Seeing failures, like losing a significant order, as opportunities to learn and evolve instead of insurmountable setbacks.
  • Persistent Effort: Understanding that mastery and improvement require time, effort, and perseverance.
  • Feedback and Critique: Welcoming constructive criticism as a resource for learning and development.
  • Learning from the Success of Others: Viewing peers and competitors as sources of knowledge and inspiration rather than threats.

Combining Fact-Based Management with a Growth Mindset

The synergy between managing by fact and fostering a growth mindset can become a formidable strategy in manufacturing. Here’s how:

  1. Data-Driven Insights for Continuous Learning: Utilising data not just for operational decisions but for learning and development, aligning employee growth with strategic business goals.
  2. Metrics for Performance and Growth: Performance metrics and KPIs can serve dual purposes—measuring current productivity and efficiency while identifying areas for skill development and innovation.
  3. Adaptability through Objective Analysis: An objective, fact-based approach empowers teams to adapt swiftly to market changes, technological advancements, and competitive dynamics, fostering a culture of continuous improvement and agility.

The Story of Resilience and Adaptation

Returning to the narrative of the SME Manufacturer, the loss of a £1.5 million order could have been a crippling blow. However, the management and team’s growth mindset, coupled with a strategic focus on facts and data, turned a potential disaster into a learning opportunity. It pushed the company to analyse what went wrong, to understand the market and competitors better, and to refine its value proposition and operations accordingly.

Their journey underscores several key takeaways for manufacturers:

  • Resilience is Key: The ability to bounce back from setbacks, powered by a belief in continuous improvement and the possibility of growth.
  • Embrace Change: Being open to change and willing to adapt strategies based on what the data shows can differentiate between stagnation and growth.
  • Collaborative Teamwork: A shared growth mindset within the team fosters collaboration, innovation, and shared ownership of both challenges and successes.

Conclusion: Forging Ahead with Facts and Growth

As the manufacturing sector continues to evolve amidst ever-changing market dynamics, the story of the SME Manufacturer serves as a compelling case study in the power of managing by facts not by emotion, and the transformative impact of a growth mindset.

Their experience illuminates a path forward for manufacturers seeking to navigate the complexities of modern-day business. It’s a dual approach where decisions are driven by data and insights, and where challenges and setbacks are seen not as endpoints but as stepping stones to greater achievements.

The manufacturers who will thrive are those who embrace the power of data, leverage the resilience of a growth mindset, and view every challenge as a new opportunity for growth and learning. Just as the SME Manufacturer demonstrated, the key lies in not just focusing on what to shrink but rather on what to grow. By striving to be better today than yesterday and planning to be better tomorrow than today, manufacturing businesses can ensure they remain competitive, innovative, and poised for success in an ever-evolving landscape.

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Funding for Manufacturers

Are you a Manufacturer?

Are you looking to make an improvement, solve a problem?

Would some funding help ease the costs?

The image illustrates all interventions covered by the EDRF Funding up to September 2021. The funding covers areas including West Midlands, Yorkshire and Humber, parts of the East Midlands, South East and East of England.

(Case Study – SME Manufacturer Leverages Funding & Increases Output)

Interventions in Scope

With up to 35% grant funding our Improvement Programme is designed to stimulate the growth of aspiring manufacturing businesses, in any sector, helping them to identify opportunities for growth, solving current problems, driving continuous improvement and increasing competitive performance.

To qualify you have to be a Manufacturer with Fewer than 250 employees and a turnover less than or equal to €50 million OR a balance sheet total less than or equal to €43 million.

Just enter your name, email address and the description of the intervention you are interested in and we’ll be in touch, it’s as easy as that.

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Get your Changeovers out of the Slow Lane

Benefits of SMED  (Single minute exchange of dies)

  • WIP and lot size reduction.
  • Finished goods inventory reduction.
  • Improved machine/resource utilisation.

Whether you are high volume or low volume business, changeovers is one of those things that can sap the living life out of your manufacturing process.

An unstructured/wasteful approach to changeovers (SMED, set-up, etc) has the uncanny ability to grow arms and legs, and those arms and legs can even grow arms and legs.

I first witnessed a set up reduction back in the early 90’s as a Kaizen Engineer manufacturing Aerospace Fasteners, we were being trained by a Japanese sensei in Lean Manufacturing, running three events on different machines; a centreless grinder; a header machine and thread roller.

Our team had the header machine, we videoed the actual set up so we could observe the waste within the process, much to our surprise there was 8 hours of it????? A WHOLE SHIFT WORTH OF CHANGEOVER for a production run that would probably last no more than 30/60mins depending on batch size, and batch size we were talking thousands. It was running three shifts.

Now bearing in mind, a major customer had flagged this as an high risk to their operation due to capacity and were forcing discussions on us purchasing another machine?????

At the start of the week, we we’re thinking a 50% reduction would be excellent, never in a million years did we think we’d get to sub 30mins, but we did!

Long Changeovers drive so much waste within your business, WIP, Overproduction, delays, waiting, transportation…..so they need to be focussed on.

The main benefits are as shown

Key Principle of SMED


Internal set up activities can only be performed when the process is stopped and must be kept to the absolute minimum in number and time taken to complete. Internal set-up activities should be limited to the actual fitting or removing of the Tool or Die or Material ONLY.


External set up activity can be performed with the process running and therefor does not affect the core changeover time.

As many changeover activities as possible should be external, leaving as few as possible as internal activities.

The statement that always sticks in my mind from my early SMED activities is ELIMINATE, COMBINE, SIMPLIFY.

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The Productivity Puzzle and Lean

I’ve never been one to shout about Lean, Six Sigma or Theory of Constraints, to individuals to solve a solution. I personally have though, applied the tools and techniques to resolve a situation or gain an opportunity I have faced. Granted, it’s not just about the application of tools and techniques, it’s equally important to focus on People, Culture and Managing Change within today’s organisations and society. Every single person has touched or been a part of a Lean process, within our everyday life from grocery shopping to our work we will have been in contact with lean in motion.

The interesting thing I have noticed recently are the articles beginning to appear regarding “is Lean at a crossroads?” and “How Lean is perceived today” particularly in the UK (but perhaps globally). An article by Morpheus Group stated “Businesses are taking a much more pragmatic approach, using a blend of tools….with very few businesses labeling their Corporate Programmes as Lean”.

It does seem that Lean and other Japanese terms associated with it are perceived a risk to alienating the workforce. I wonder why? Are we that uncomfortable with something that is not invented by us?? Are we hiding behind the terms as an excuse not to change??? (There is no doubting it is hard to implement and sustain, but that should never be an excuse). When I personally think about these questions it’s never been about the wording (don’t get me wrong I do cringe with some of them) but it’s about the application, execution/implementation that is key and the right behaviours that drive it so that we can benefit from it.

Businesses are placing a lot of importance on Strategic Cost Saving and Quality. This is absolutely fundamental in “Change” for any business. Strategy and Performance Management, Policy Deployment, Hoshin Kanri, whatever you choose to call it, is the back bone of your business, it is how you do business.

I believe Business Improvement is more important today than it ever has been with the globalisation of markets. What is it that gives us the competitive edge? In particular UK Productivity remains below pre-recession levels. I have been in discussion groups where an estimated 40% of productivity is lost through non value added activities, an estimated £3 Billion cost. Something Lean, Six Sigma, TOC can certainly impact.

This debate will carry on and involves so much from skills, impact on society, etc., etc.

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