The reality of the fourth industrial revolution

With the third industrial revolution taking place in 1969, we saw the move from mechanical and analogue systems to computerised systems where the notable use of robotics and automation took place, with General Motors famously being the first to implement them onto the factory floor using a supplier called Unimation. This technological leap provided manufacturers the opportunity to accelerate productivity as they could now leverage continuously running robotics and automation in hazardous environments, whilst lowering workplace injuries and reducing raw material waste for high-precision tasks.

The current digital state of play

The use of robotics and other digital products is common across the manufacturing industry. If you look through the window of an automotive manufacturing facility, you’ll see armies of robots assembling the latest vehicle model in unison. If you walked onto a chemical manufacturing facility, you’d see operators using sensors and gauges to guide them through the process – when to perform their next action at the optimum time, and whether or not there is an error occurring within the process.

However, with these advancements came new problems. Let’s take Internet of Things (IoT) sensors for example. IoT sensors are prevalent within the manufacturing world as the data they provide can provide insight into both the entire end-to-end process, as well as the condition and stage of a particular process such as temperature, pressure or humidity. However, these sensors need consistent maintenance and continuously produce a lot of data, causing a high degree of data volume and velocity. During my time in the administrative department within a large manufacturer, I can say from first-hand experience that the maintenance of these sensors was hap-hazard, following a schedule that had to be changed every other month – usually built upon incomplete data – and not necessarily digitised and producing data, but rather analogue sensors at best linked to an alarm. Whilst this was inefficient, it still worked, but it could have been a lot better.

The fourth industrial revolution

If we look ahead beyond manufacturing 3.0, we see the vision of manufacturing 4.0 – or the fourth industrial revolution – which is described as the next stage of digitisation within the manufacturing industry. Technologies consisting of high-capacity connectivity, machine learning and other artificial intelligence applications, are driven by breakthroughs in multiple fields such as nanotechnology, AI, 3D printing, energy storage and material science. The end-to-end implementation of these technologies is culminating into the vision of the ‘hyper-connected value network’, where the idea of manufacturing 4.0 extends beyond the manufacturer, and into the wider supply chain through seamless data sharing.

A Lighthouse facility network for scale

A phrase that has been coined by the World Economic Forum is ‘lighthouse facility within the global lighthouse network’, and is reserved for manufacturers that have achieved this type of set up at scale, with massive operational and financial benefits such as Tata Steel India, GlaxoSmithKline and Henkel. Whilst more and more facilities are joining every year, currently only 153 facilities are recognised as lighthouses as there is a global lag in terms of manufacturing 4.0 technology adoption. The network aims to aid others in scaling operations, and have worked in collaboration to develop frameworks and best practices in order to help with the adoption and deployment of these solutions.

The problem here, however, is that there is a lot of ambition to perform transformational projects using this bleeding edge smart tech, but the reality is that it isn’t necessarily translating to anything tangible for most manufacturers.

This isn’t because there is a lack of talent or drive, but rather it’s a highly complicated field with a huge array of disciplines being leveraged. With 70% of manufacturers experiencing ‘pilot purgatory’ – where they can’t scale beyond a single use case or process – it’s clear to see that implementation difficulties are plaguing aspiring businesses across the board. If we look at existing lighthouse facilities, we notice that the majority of these facilities are greenfield projects – not brownfield – meaning it’s easier to create these facilities from the ground up, instead of ripping out an existing process and replacing it with a new one. Also, if we analyse previous industrial revolutions, we’ll see that each evolution encompassed a complex array of transformations across economic, social, and political stages. That said, an argument could be made that the twenty-first century is different as the advancements within cloud computing brings together diverse data, and this pairing of data – not necessarily technological advancements – is what’s distinctive.

The complexities behind manufacturing 4.0

We need to consider that the manufacturing process is continuous, and it's estimated that for every hour of downtime within a manufacturing plant, is a loss of up to £7,500 – and this doesn’t account for impacts to the wider supply chain, labour cost, hardware replacements and penalties imposed by customers for late orders either. So how are manufacturers reasonably expected to rip up their manufacturing process to implement smart technologies, without causing disruption to both themselves and the rest of the supply chain? How do you hire for the new required skills? How do you adjust your capacity alongside the requirements and needs of the supply chain?

The barriers to manufacturing 4.0 are complicated, and are a mixture of cultural, process and technological challenges:

• Legacy infrastructure is commonplace and results in technical debt and a lack of capability to support workloads. With the manufacturing process being continuous, the removal of existing systems that the teams are familiar with, and with new skills required to leverage cloud technologies with no guarantee of reliability, is a worrying prospect for some
• A lack of a cohesive vision can cause a pull in multiple directions, ultimately leading to nothing being launched successfully
• A scepticism from some over the Return on Investment these technologies bring
• Data interoperability across solutions such as IT and OT (Operational Technology), and the security and ownership of that data, and difference of standardised formats between partners can cause apprehension
• Cultural resistance amongst workers worried about displacement or shifting of their responsibilities as with new technologies come new skill requirements.

Whilst in large it’s true that to see the massive, exponential benefits from these solutions, they need to work together end-to-end across the entire manufacturing facility. However it isn’t to say that alone these parts are worthless. There are still large tangible gains to be felt by adopting smaller deployments of technology within certain use cases.

Leveraging technological advancements, without disruption

If we look at what manufacturers want to do across the board, it can broadly be defined as identifying opportunities for improvement, develop new products and services, manage performance and optimise business processes. None of these elements realistically require a raft of shiny bleeding edge technology to make notable gains within these areas.

For example, implementing a streaming solution that provides visibility and analytics on IoT sensors will still provide operational teams visibility of when sensors may break, be causing a bottleneck, or allow you to better audit the manufacturing process to make improvements. The next step beyond that may be to implement a machine learning solution using the data gathered from these sensors to provide predictive maintenance, improving how your engineers wrench time is assigned amongst a whole host of impactful use cases.

Whilst the vision of implementing manufacturing 4.0 remains intangible for many, there are still lots of highly impactful use cases and initiatives that can leverage these technologies today, without causing large scale disruption to either the factory operations or the carefully cultivated cultural ecosystem.

If you’re looking to understand more about how data and AI can play a pivotal part in your business operations, speak to one of our team of data experts.