From Dickens to the Jetsons: forget the crystal ball

Predicting the future of manufacturing gives analysts something to do, but only the nurturing of talent and flexibility can truly create a future-ready enterprise.

Predicting the future has always been fraught with danger (and risk of embarrassment), as hindsight shows. But, when it comes to ‘smart manufacturing’, there is no shortage of future prediction going on at the moment.

While advances in technology, particularly around the Internet of Things and AI, have been held up as changing the world of manufacturing in the future for some years now, the ‘real’ external world outside the world of automation is also having an impact on how we see the future of automation panning out.

As the mysterious Chinese philosopher Lau Tzu pointed out in the 6th century BCE: “Those who have knowledge don’t predict. Those who predict don’t have knowledge.”

Sorting through the ‘chicken entrails’ of IIoT, digitisation, big data analytics, artificial intelligence and machine learning, and trying to combine them with the dice-rolling of economic prediction in a post-Trump global market, is difficult. However, the crystal ball gazers are ever present, and when it comes to smart manufacturing, they have been promising a lot of change — at least certain types of change.

In thinking about this article, I have read a number of recent white papers about future manufacturing. These tend to be produced, not by people in the industries they discuss, but by industry analysts in their city offices, looking from afar at the “global landscape” with the eyes of an all-seeing deity it would seem.

So let’s have a look at what they are saying.

Mass customisation

This one has been a big topic ever since the idea of ‘batch size 1’ was proposed some years back. While it is difficult to expect totally individual single-item batches happening tomorrow, most prognosticators are predicting that within the next 10 to 15 years, factories and plants across multiple sectors will be “high-tech engines of mass customization, able to respond quickly and effectively to changing customer and market demands”¹.

Here is another quote:

“Highly automated and information-intensive, the factory of tomorrow will look like an integrated hardware and software system. This system will be fuelled by vast quantities of information from every corner of the enterprise and beyond, moderated by analytical systems that can identify and extract insights and opportunities from that information, and comprised of intelligent machines that learn, act, and work alongside highly skilled human beings in safe and collaborative environments.”

As no doubt the readers of this publication all know, this statement seems to be based on a particular image of a ‘factory’ that someone might have if they had never stepped into one — and perhaps only one kind of factory: one that makes discrete manufactured solid objects.

But a ‘factory’ could be making ‘objects’ from automobiles to smartphones to plastic toothbrushes or children’s toys — or anything from medicinal tablets to biscuits or beer. Or maybe it is a continuous process plant processing petroleum or gas, crushing rocks and refining ore, or creating the plastics needed for the cars, toothbrushes and toys. After all, they are all part of the economy and supply chain in the world of manufacturing. And these different industries have different relationships to ‘big data’ and are impacted by external forces, each in different ways.

Or there’s this quote from the same authors:

“Today’s image of manufacturing as a dark, dirty, and unattractive place to work will give way to a bright and exciting new reality. This reality is in the early stages of formation today as trends such as connectivity and networking, information and process digitization, advanced analytics and computing, and new models of production like 3D printing take hold and play out.”

It looks like we’re moving from the Victorian world of Oliver Twist to the robot-served world of the Jetsons (bright and exciting flying Ubers notwithstanding).

Autonomous factories

Writers from within the automation industry take a different tone. Recently we published an article by ABB on what would be necessary to create an autonomous plant, operating in much the same way as an autonomous vehicle.

In ‘The road from automation to autonomous systems’², the author describes the first step to autonomy as being ‘autonomous engineering’, in which it is first necessary for a plant or processing system to have the ability to make adjustments to its own configuration in real time. Only then can autonomous control be possible, eliminating human error, by replacing what are now human operational decisions with those activated by artificial intelligence.

However, the vision of an autonomous factory of the size we see today seems a fair way off: the sheer complexity of a plant such as an automobile factory will mean the need for some rethinking of how manufacturing plants operate now.

Federated manufacturing

The Frost & Sullivan report quoted above actually proposed the concept of federated manufacturing, based on “the establishment of so-called micro-factories that, for example, will enable significant levels of personalization using 3-D printing and digital manufacturing techniques”.

Taking advantage of today’s more networked social and business environment, federated manufacturing implies a move away from the centralised operations of today towards an on-demand manufacturing model. Manufacturers will find ways to shorten the production and delivery cycle, removing the need for large centralised manufacturing facilities.

There are already examples of federated manufacturing beginning to occur. One example found in the literature is the small automotive manufacturer Local Motors. The company describes itself as “a ground mobility company focused on shaping the future for the better…with a belief in open collaboration and co-creation”. As far back as 2007, the company “began low volume vehicle manufacturing of open-source designs using multiple micro-factories”.

A viewing of the company’s website speaks for itself³, with a Guinness World Record-breaking rally car, an autonomous mini-bus (known as Olli, already operating in Glenelg, South Australia), a Domino’s Pizza delivery vehicle and custom-built military vehicles among the list of the company’s achievements. Through micro-manufacturing, Local Motors gets its products to customers up to 24 times faster than traditional manufacturing processes.

According to realityweb.com, there is already evidence of changes to operations and maintenance models that will enable federated manufacturing⁴.

“More original equipment manufacturers (OEMs) are exploring or migrating to hardware as a service (HaaS). With HaaS, the OEM leases the industrial machinery to the manufacturing plant and services its own equipment.”

With the ongoing reduction in the cost of connectivity, storage and computational power, machine learning is being applied to data derived from machine sensors, detecting anomalous behaviour, and allowing the HaaS OEM to provide the necessary pre-emptive maintenance to their hardware on the manufacturer’s site. Automated machine learning through AI enables these companies to scale their operations to many machines at many sites.

Global economic influences

Surveys on the subject of federated manufacturing seem to indicate that many believe that such Industry 4.0 manufacturing models will lead to a slowdown in the trend towards relocating to low-wage countries; however, in a rapidly changing and increasingly interconnected global market this may not be the case. The reality today is more complex than a simplistic east/west dichotomy.

In an article for Forbes in 2018, Marco Annunziata⁵ wrote of the change in global markets over the last 20 years:

“In 1995, advanced economies accounted for about 60% of global GDP, and emerging markets only 40%. Those shares have now reversed: emerging markets today make up more than half of the global economy. Global trade helped them lift hundreds of millions out of poverty and create a middle class; the process supported stronger economic growth across the globe.”

The traditionally more protectionist behaviours of large economies like China have now influenced other advanced economies to retaliate in kind, most notably the United States. In addition, the changing market demographics are having an influence. In 2018, banking executive Peter Wong wrote an article in the South China Morning Post⁶ that compares the growth of the middle class in Asia to the post-World War II growth of the middle class in the West:

“By 2030, it is forecasted that two-thirds of the global middle class will be living in Asia. In contrast, North America and Europe will together account for only a fifth of the world’s middle-class population, down from more than half in 2010.” If a disruption in the growth of the Asian middle class should occur, both mature and emerging markets could be detrimentally affected.

Preparing for the future

As a result of these global forces, pragmatic business leaders need to take practical steps to adapt to the changing world economic landscape, and cushion their businesses from economic shocks. Modern automation technology and emerging concepts like federated manufacturing may provide the necessary agility that businesses need:

• Federated manufacturing, supported by additive manufacturing processes and the IIoT, will allow companies to operate efficiently at smaller scale, gaining flexibility in how they localise production.
• In larger markets such as Europe and the US, companies can build local supply chains, better nurturing domestic business relationships.
• Digital twin technologies can help companies better manage not only their plants, but also their supply chains, even being able to simulate disruption and better prepare for shocks.
• Countries with strong education and training programs, and an immigration policy that attracts talent, will have a competitive edge — something that Australia needs to remedy in short order. The nurturing of talent is an imperative now to prepare for the future.
   

Albert Einstein once said: “I never think of the future, it comes soon enough.” However, while the ivory tower prognosticators wax lyrical about a Jetsons future, there must be a middle ground that needs to be found.

The future cannot be predicted, because it doesn’t exist except as ideas. And while it has always been true that the most flexible tend to weather any storm, now more than ever, planning for flexibility and agility would seem to be the first best option — and investing in emerging technologies in automation and process control may well be the recipe needed to do it.

References

1. Frost & Sullivan 2017, Vision 2030: The Factory of the Future.
2. ABB Australia 2019, ‘The road from automation to autonomous systems’, Process Technology, vol. 33, no. 6, November 2019, <<https://www.processonline.com.au/content/software-it/article/the-road-from-automation-to-autonomous-systems-1340109904>>
3. Local Motors 2019, <<https://localmotors.com/>>
4. realityweb.com 2019, ‘The Impact of Federated Manufacturing on the Industrial Sector’, <<https://reliabilityweb.com/articles/entry/the-impact-of-federated-manufacturing-on-the-industrial-sector>>
5. Annunziata M 2018, ‘Tech Vs Tariffs: How Companies Adapt To A Protectionist World’, Forbes <<https://www.forbes.com/sites/marcoannunziata/2018/03/22/tech-vs-tariffs-how-companies-adapt-to-a-protectionist-world>>
6. Wong P 2018, 'Made in Asia for Asia: How the rise of its middle class is remaking the world economy', South China Morning Post, <<https://www.scmp.com/comment/insight-opinion/article/2087687/made-asia-asia-how-rise-its-middle-class-remaking-world>>

Image: ©stock.adobe.com/au/Monopoly919