May 16, 2020

Overcoming AI and Machine Learning barriers in manufacturing

Smart Manufacturing
Matt Newton
4 min
Artificial Intelligence
Matt Newton, Senior Portfolio Marketing Manager at AVEVA, details the ways in which manufacturers can overcome AI and ML adoption barriers.

There has b...

Matt Newton, Senior Portfolio Marketing Manager at AVEVA, details the ways in which manufacturers can overcome AI and ML adoption barriers.

There has been a considerable amount of hype around Artificial Intelligence (AI) and Machine Learning (ML) technologies in the last five or so years. So much so that AI has become somewhat of a buzzword – full of ideas and promise, but something that is quite tricky to execute in practice.

At present, this means that the challenge we run into with AI and ML is a healthy dose of skepticism. For example, we’ve seen several large companies adopt these capabilities, often announcing they intend to revolutionize operations and output with such technologies but then failing to deliver. In turn, the ongoing evolution and adoption of these technologies is consequently knocked back. With so many potential applications for AI and ML it can be daunting to identify opportunities for technology adoption that can demonstrate real and quantifiable return on investment.

Many industries have effectively reached a sticking point in their adoption of AI and ML technologies. Typically, this has been driven by unproven start-up companies delivering some type of open source technology and placing a flashy exterior around it, and then relying on a customer to act as a development partner for it.

However, this is the primary problem – customers are not looking for prototype and unproven software to run their industrial operations. Instead of offering a revolutionary digital experience, many companies are continuing to fuel their initial skepticism of AI and ML by providing poorly planned pilot projects that often land the company in a stalled position of pilot purgatory, continuous feature creep and a regular rollout of new beta versions of software. This practice of the never ending pilot project is driving a reluctance for customers to then engage further with innovative companies who are truly driving digital transformation in their sector with proven AI and ML technology.

Innovation with direction

A way to overcome these challenges is to demonstrate proof points to the customer. This means showing how AI and ML technologies are real and are exactly like we’d imagine them to be. Naturally, some companies have better adopted AI and ML than others, but since much of this technology is so new, many are still struggling to identify when and where to apply it.

For example, many are keen to use AI to track customer interests and needs. In fact, even greater value can be discovered when applying AI in the form of predictive asset analytics on pieces of industrial process control and manufacturing equipment. AI and ML can provide detailed, real-time insights on machinery operations, exposing new insights that humans cannot necessarily spot. Insights that can drive huge impact on businesses bottom line.


AI and ML is becoming incredibly popular in manufacturing industries, with advanced operations analysis often being driven by AI. Many are taking these technologies and applying it to their operating experiences to see where economic savings can be made. All organizations want to save money where they can and with AI making this possible. These same organizations are usually keen to invest in further digital technologies. Successfully implementing an AI or ML technology can significantly reduce OPEX and further fuel the digital transformation of an overall enterprise.

Industrial impact

Understandably, we are seeing the value of AI and ML best demonstrated in the manufacturing sector in both process and batch automation. For example, using AI to figure out how to optimize the process to achieve higher production yields and improve production quality. For example, in the food and beverage sectors, AI is being used to monitor production line oven temperatures, flagging anomalies - including moisture, stack height and color - in a continually optimized process to reach the coveted golden batch.

The other side of this is to use predictive maintenance to monitor the behavior of equipment and improve operational safety and asset reliability. A combination of both AI and ML is fused together to create predictive and prescriptive maintenance. Where AI is used to spot anomalies in the behavior of assets and recommended solution is prescribed to remediate potential equipment failure. Predictive and Prescriptive maintenance assist with reducing pressure on O&M costs, improving safety, and reducing unplanned shutdowns.

Technological relations

Both AI, machine learning and predictive maintenance technologies are enabling new connections to be made within the production line, offering new insights and suggestions for future operations.

Now is the time for organizations to realize that this adoption and innovation is offering new clarity on the relationship between different elements of the production cycle - paving the way for new methods to create better products at both faster speeds and lower costs.


For more information on manufacturing topics - please take a look at the latest edition of Manufacturing Global.

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Jun 8, 2021

IMF: Variants Can Still Hurt Manufacturing Recovery

Elise Leise
3 min
The International Monetary Fund (IMF) claims that while markets are rising and manufacturing is coming back, it’ll push for global immunisation

After a year of on-and-off manufacturing in the US, UK, and the eurozone, demand for goods surged early last week. Factories set growth records in April and May, suppliers started to recover, and US crude hit its highest price point since pre-COVID. As vaccination efforts immunise much of the US and UK populations, manufacturers are now able to fully ramp up their supply chains. In fact, GDP growth could approach double-digits by 2022

Now, the ISM productivity measure has surpassed the 50-point mark that separates industry expansion from contraction. Since U.S. president Biden passed his US$1.9tn stimulus package and the UK purchasing managers index (PMI) increased to 65.6, both sides of the Atlantic are facing a much-welcomed manufacturing recovery. 

Lingering Concerns Over COVID

Even as Spain, France, Italy, and Germany race to catch up, and mining companies pushed the FTSE 100 index of list shares to a monthly high of 7,129, some say that UK and US markets still suffer from a lack of confidence in raw material supplies. Yes, the Dow Jones has made up its 19,173-point crash of March 2020, and MSCI’s global stock index is at an all-time high. 

Yet manufacturers around the world realise that these wins will be short-lived until pandemic supply chain bottlenecks are solved. If we keep the status quo, consumers will pay the price. In April, inflation in Germany reached 2.4%, and across the EU’s 19 member countries, overall prices have increased at an unusual pace. Some ask: Is this true recovery? 

IMF: Current Boom Could Falter

Even as Elon Musk tweeted about chip shortages forcing Tesla to raise its prices, UK mining demand skyrocketed; housing markets lifted; and the pound sterling gained value. The International Monetary Fund (IMF), however, cautioned that manufacturing recovery won’t last long if COVID mutates into forms our vaccinations can’t touch. Kristalina Georgieva, Washington’s IMF director, noted that fewer than 1% of African citizens have been vaccinated: “Worldwide access to vaccines offers the best hope for stopping the coronavirus pandemic, saving lives, and securing a broad-based economic recovery”. 

Across the globe, manufacturing companies are keeping a watchful eye on new developments in the spread of COVID. Though US FDA officials don’t think we’ll have to “start at square one” with new vaccines, the March 2021 World Economic Outlook states that “high uncertainty” surrounds the projected 6% global growth. Continued manufacturing success will in large part depend on “the path of the pandemic, the effectiveness of policy support, and the evolution of financial conditions”. 

Mathias Cormann, secretary-general of the Organisation for Economic Co-Operation and Development (OECD) concurred—without global immunisation, the estimated economic boom expected by 2025 could go kaput. “We need to...pursue an all-out effort to reach the entire world population”, Australia’s finance minister added. US$50bn to end COVID across the world, they imply, is a small investment to restart our economies.

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