But sometimes the exact opposite happens. That’s certainly the case for Jendamark and our journey with our own digital solutions. As Yanesh Naidoo explains in this article, factory floors in Germany, the USA and South Africa have more in common than you might think.
Some of the world’s most practical manufacturing technologies emerge from environments where constraints are greatest. This is because factories in emerging markets are often more willing to rethink established processes or adopt new technologies because they are less constrained by legacy infrastructure – and more in need of results to stay competitive.
In South Africa, where Jendamark was founded, our manufacturing sector has long operated under specific pressures, forcing companies to solve problems that many developed economies are only just beginning to encounter.
Here, we have a saying: “’n Boer maak ‘n plan” (a farmer makes a plan), which means that when we encounter a problem that doesn’t have a ready-made fix, we build the solution with the resources we have.
A great example is the customer challenge that led to the start of our ODIN digital solutions more than two decades ago. The customer said: “Oh by the way, we need to make something that changes the worker guidance sheets because many of our operators can’t read, and also the part is changing all the time, are you guys keen?”
Of course, we said yes, and decided to try something we had never done before. But how to solve a skills problem, a variability problem, and a complexity problem in one? What began as a worker guidance solution for a South African assembly line is now addressing workforce and production challenges across Europe, North America and beyond.
Something we realised very early on is that it’s often good to be close to the problem, because it leads to a better understanding of what needs to be solved – and that’s where the opportunity lies.
Jendamark’s core business is developing automotive component assembly systems for a variety of operating environments – from manual to fully automated processes, in labour-driven and lights-out factories, with varying operator control and skill levels.
So, our original challenge was not to build software, but to make complex manufacturing possible and efficient under difficult conditions. And the result was ODIN.
Since the early 2000s, automotive manufacturing has become increasingly complex. The sheer number of vehicle options and new technologies spawned a factory environment that now has to accommodate high-precision assembly, high variation, and fluctuating volumes.
Operators need to build a range of variants correctly first time, every single time. Traditional paper-based work instructions are no longer sufficient, and it’s particularly challenging where operators have low levels of literacy or are not reading in their home language.
So, how do you ensure the correct assembly process is followed when:
The first version of ODIN Workstation introduced dynamic worker guidance driven directly from production data, based on the Bill of Materials (BOM). No more paper or relying on experience and memory, just a step-by-step visual breakdown of each assembly process on a computer screen.
That’s how we solved the immediate challenge in South Africa, and saw the opportunity to eventually export it globally.
So what does a South African-born company understand about the challenges facing advanced European and North American manufacturers? Should we be confining our expertise to developing nations more like ourselves, like India?
The answer is that we understand the skills gap problem on all factory floors. It might have a different root cause but the outcome is exactly the same.
In Germany, for example, the experienced workforce is ageing into retirement, leaving a void that the younger generation shows little to no interest in filling.
The United States, on the other hand, has a high workforce turnover in factories and, like Europe, a growing dependence on immigrant labour, resulting in an increasingly multilingual working environment, where operators are not receiving instructions in their home language.
In South Africa, we have worked to overcome our own language barriers and skills shortages – stemming from educational gaps and limited access to specialised training. So, we understand the basic question that manufacturers everywhere are asking:
How do we ensure consistent quality when workforce experience, language and skill levels vary?
The answer increasingly relies on intelligent worker guidance systems, so we’ve continued to develop our basic ODIN solution to respond to what is essentially a growing global skills challenge.
The speed with which modern manufacturing moves means that extensive training is no longer feasible. Operators can’t commit every process to memory and, as workforce turnover increases, the manufacturing systems must give access to knowledge exactly when and where it is needed.
More than this, our ODIN Workstation, has had to evolve accordingly from simple digital work instructions and visual guidance to a more holistic assembly line operating system that can validate decisions or detect mistakes in real time, and adjust instructions dynamically to keep production on track. (Similar to how Google Maps reroutes after you take a wrong turn.)
The result is not less capable individuals but rather more consistent capability across the workforce.
An important point to emphasise here is that the purpose of digital guidance is not to “dumb down” work or to replace operators. Our guiding principle is that technology should act as safety net that reduces the risk of human error, improves product quality, supports operators and creates confidence in the whole production process.
One of the most overlooked benefits of intelligent manufacturing systems is protection for workers, not just in the physical sense of improved safety, but by creating clear audit trails, so that there is accountability and protection against unfair blame when issues occur downstream.
The technologies that solve these challenges are no longer being developed exclusively in the highly industrialised nations. ODIN’s journey is one example of a broader truth: innovation often starts at the edge, long before the rest of the world realises it has the same central problem.
To see how our AI factory agents bridge language barriers, watch the video below.
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