Manufacturing Matters- Tuesday Top-Up 78

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• What’s Been Happening in our MAKE│NZ Community
• Future Events
• News From The World of Manufacturing
• Other News of Interest to Manufacturers
• Fun Facts

What’s Been Happening in our MAKE│NZ Community

Have you got your tickets?

At the Auckland Showgrounds, to kick off EMEX 2026, May 26th we’ll be hosting a full day conference. We’ll be running through a rich programme of case studies, reviews, and practical insights, delving into AI, Industry 4.0 integration, robotics and human‑robot collaboration, future‑ready skills, and workforce upskilling. Complementing this are sessions on growing manufacturing start‑ups, preparing investors and owners for new opportunities, and navigating succession—whether passing the business to the next generation, merging for scale, or aligning with international buyers.

If you want to hear from speakers from the likes of Dawn Aerospace, Galin Engine, Buckley Systems, and more? You know what you need to do.

You can find the programme, special discounts, and more HERE

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Future Events

• Reminder: our next Fireside Chat on May 11 will be showcasing the PV (photo voltaic) installation on the roof of Hamilton Jet’s new factory building. We’ll hear from Steve Lockhart, Manufacturing Engineering Manager at Hamilton Jet, and Andy Wells, MD at Sunergy Solar, who worked with Hamilton Jet on the project.

If you haven’t received an invitation for this event (yet), it’s probably because you are not a member of MAKE│NZ. To join, or enquire about becoming a member, please contact Sabine at sabine@makenz.org .

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News From The World of Manufacturing

•Since this is from a letter from the UK, let’s look at how manufacturing in the UK is doing.

New data, released on April 23, shows that after a slight retreat (still in positive territory above 50) in March, the PMI for April was up by 2.6 points – a significant increase. All good news then?

Behind the scenes, there are reports from a number of manufacturers that the rise in sales is mainly due to orders being brought forward in the expectation of rising input prices and supply constraints. At the same time reports are getting more common of increases in vendor lead times and some raw material shortages and international shipping disruptions, all weighing on production volumes in April.

The other significant news was a steep increase in input prices (other than labour) that was not matched by prices for goods sold – very much the picture painted by manufacturers back in New Zealand.

Looking at different subsectors of UK manufacturing, Consumer Goods manufacturers reported solid growth in both production and new orders. Likewise, manufacturers of Capital Goods (machinery and equipment) also returned to growth in April after a period of volatility, with clients bringing orders forward amid fears of rising transport costs and supply shortages. Finally, sectors focused on Digital Transformation and Automation are seeing high levels of activity as their clients look to offset rising labour costs and a shortage of skilled labour.

On the negative side, manufacturers of intermediate goods reported being squeezed between rising raw material costs (oil, chemicals, and metals) and weakening demand from smaller domestic clients.

As is the case in New Zealand, output for manufacturers of construction materials has fallen sharply. Persistent high interest rates and a slowdown in major infrastructure projects have stifled demand for bricks, cement, and steel, among others.

Segments of food & beverage manufacturing requiring high levels of process heat are struggling with margin erosion. The manufacture of beverages, in particular, has seen a noted drop in output due to increased transport and packaging costs.

Finally, while large firms are doing well in some areas, SME manufacturers across all sub-sectors of manufacturing are still reporting declines in both production and new orders. They lack the scale to absorb the “surging” input costs which reached the fastest rate of inflation since late 2022.

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Other news of interest to manufacturers

•To say that we currently experience a less stable economic environment would probably be classed as a gross understatement – and not only since the recent Gulf War was started. And yet – and maybe because of that uncertainty – many feel called upon to make predictions about the future of our own economy, and that of other countries. Futhermore, when we read and listen carefully, we will find that many of these predictions are based on ‘linear thinking’ – a straight-line extrapolation of current and the most recent past developments. “We have revised our OCR forecast and now expect three consecutive 25bp hikes in July, September and October, taking the OCR to 3%.” That’s the prediction of ANZ economists in their most recent economic research data wrap of April 17. Or take this example of an Australian analyst’s prediction of future crude oil and gas supplies. And then there’s this comment from the quite aptly named Samantha Dart, Co-head of Goldman Sachs Global Commodity Research in a recent Bloomberg interview, explaining why oil prices can be expected to remain at a high level at least until the end of 2026: “All of these are reasons why the back-end [end of year price of crude oil] should be higher the longer this drags. But … some things have looked a little bit different versus what we have expected over the past few weeks. One, we’re seeing a smaller curtailment of oil production versus what we expected. The second factor that I would say is a little bit different is demand destruction that is proving to be higher than what we expected as well …” – a concession here that linear, or even simple non-linear predictions, don’t always describe actual outcomes.

What is sitting behind our human preference for straight-line extrapolation? We could start with an analogy. Albert Einstein, whose scientific curiosity extended well beyond pure physics, wrote a paper just over 100 years ago, explaining why meandering rivers are so common in nature when the path of least resistance for water is running straight downhill.

Starting with a tea-in-a-cup analogy, Einstein explained a river meanders via secondary flows that shift high‑velocity water toward the outer bank, causing asymmetric erosion and downstream migration of bends:

Einstein’s paper laid a foundation, but the physical, geophysical, and geological mechanisms behind meandering are much more complicated and still not completely understood.

What we can learn from this analogy is that in nature minor forces that cause rivers to no longer run straight are at work all the time. Individually, these forces and their impact are hard to identify, collectively they form a complicated web of actions and interactions that make the behaviour of such systems hard to predict.

Macroeconomic processes and systems, and those that determine success or failure in individual businesses, are no different in their behaviour. And yet we are intuitively drawn towards reductionism and extrapolation based on linear or, at best, simple exponential models – why is that?

The first part of the explanation deals with the fact that the evolutionary adaptation of our brains and our way of thinking is increasingly out of step with the world we live in (The “Savannah” Brain). For the vast majority of human history, our survival depended on predicting linear motion. If a predator was running toward you at a certain speed, or if you threw a spear at a moving target, your brain needed to calculate a trajectory based on constant velocity.

The second piece of the puzzle deals with physiological and biochemical processes in our brain. Thinking is “expensive” in terms of metabolic energy. To save power, the brain uses heuristics—mental shortcuts that allow us to make quick decisions:

• The Straight-Line Intuition: Linear extrapolation is the “path of least resistance.”
• Anchoring: We tend to “anchor” our predictions for the future on the immediate past. Because yesterday looked a lot like today, we subconsciously assume tomorrow will look like a slightly updated version of today.

A third factor is the lack of sensory feedback. We struggle with non-linear developments because we cannot “see” them until they reach an inflection point or breaking point. As every Angel or other investor in a start-up business will tell you, the early stages of what may develop into exponential growth in revenue look close to linear and pretty flat.

And, finally, there is the availability bias. We tend to judge the probability of an event based on how easily examples come to mind. Most of our personal life experiences—like aging, physical movement, career development and many others are experienced as linear processes. Since we have a vast internal library of linear experiences and very few “felt” experiences of non-linear growth, our brains default to the most “available” model when projecting into the future.

In reality, our understanding of brain function has progressed in leaps and bounds over the past decade in particular. We know that the processes and functions behind linear thinking in different parts of the brain are far more complicated than described above. However, and from a practical perspective, the details are far less relevant in our daily planning than the need to recognise that we are prone to apply linear thinking when we plan.

A simple way around that is scenario planning. It still involves linear extrapolation, but examines the impact of different assumptions on projected outcomes. A critical success factor here is that these assumptions are shaped by the key parameters that determine the success of your business.

The greater the (perceived) uncertainty of future developments, the more important it is that we get our planning right …

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Fun Facts (some of them not so funny)

•Most of us will be familiar with the difference between spot and futures prices for electricity in New Zealand – sometimes the gap between the two is quite big, and both are influenced strongly by seasonal balances between supply and demand.

For the trade in crude oil, gaps between spot and three-month futures prices, for example, are quite small in a stable market environment. Not so more recently:

•We’ve talked before about how the blockade of the Strait of Hormuz impacts supply chains in quite specific and critical ways. Here is another example: Europe imports 62% of its cyclohexane, required in the plastics and synthetic fibres industry, from oil refineries in the Gulf region, mainly Saudi Arabia. Cyclohexane is a critical ingredient in, among others, the manufacture of high-quality nylon fibres. It is oxidised to produce Adipic Acid and Caprolactam, which are key ingredients in the production of Nylon 6/6 (used in carpets, airbags, and car parts – adipic acid) and Nylon 6 (used in apparel and heavy-duty ropes – Caprolactam), respectively. Replacing cyclohexane in the production of these fibres with a drop-in product is not a realistic option in the short term at least, both for reasons of specific manufacturing processes and product technical features.

Saudi Arabia may have means to maintain the export of some cyclohexane through its Red Sea ports, but significant disruptions in the export of this critical intermediate compound to Europe will be inevitable.

•The robots are coming – last week it was winning a Beijing half-marathon, even though not every’body’ made it to the finish line …

This week it’s ping-pong:

You can watch the full-length video here, or a short clip here.

Less spectacular, but probably of as much if not more interest to manufacturers, is a robot that can peel fruit and vegetables, developed by researchers at the idiap Research institute in Lausanne (Switzerland):

The three researchers involved describe how they overcame the “fundamental challenge for task transfer in robotics: Unlike planar surfaces, curved surfaces do not admit a global reference frame. As a result, task-relevant directions such as “toward” or “along” the surface vary with position and geometry, making object-centric tasks difficult to transfer across shapes.”

And further, by way of introduction: “Humans routinely interact with curved objects as part of daily life, for example, when slicing a banana, peeling a cucumber, or washing dishes. These tasks require continuous physical interaction with the object’s surface, often involving making and breaking contact at different regions. In such tasks, motion on (or near) the surface is guided by the pose and geometry of the object. We refer to these interactions as object-centric tasks. Unlike collision avoidance, where simplified approximations are often sufficient, object-centric manipulation that involves physical interactions demands representations that accurately capture surface geometry and exploit its structure. A core challenge in these tasks is the immense variability in object shape. Even in a single category—such as cups or bananas—geometries can differ substantially in curvature, topology, and proportions. This variability makes it infeasible to learn and store manipulation strategies for every possible shape.”