Of course, it all started in our industry. Automation, that is. Let’s call it “Industry 1.0”. In 1805, Jacquard was granted a patent for an automatic loom controlled by punch cards. Together with steam and water power, this event triggered a hand-off from manual labour to machines that continues today. As Industry 1.0 has evolved into Industry 4.0, more and more processes have been taken over by machines of greater sophistication.

The word “automation” only caught on in the late 1940s, but there was rapid development. The first industrial robots in the fifties. Programmable logic controllers in the sixties. Material Requirement Planning (MRP), Supervisory Control and Data Acquisition (SCADA), and numerical control in the seventies. MRP II in the eighties. Machine vision in production lines in the eighties. Widespread Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES) adoption in the 90s. Business Process Automation (BPA), Collaborative Robots (Cobots), and autonomous vehicles in the 2000s.

Technological innovation continues apace, but capital expenditure on automation still has to satisfy a business need. Yes, there are clear gains from increased productivity and reduced errors. But to quote from Forbes, “companies need to be able to respond to volatile demand, uncertain supply and constrained capacity. As we look beyond the pandemic, they must also be able to respond to demanding customers who will look for individualised and sustainable products.”

In addition, developments such as process visualisation, digital twins, virtual commissioning, and predictive maintenance mean that savings in cost and time are only part of the picture when it comes to the business case.

The industry does appear to be entering a period of hyper-automation: if it can be automated, then do it. So, what are the key trends?

  1. Smarter factories based on open standards: further development of Industry 4.0 demands more open, “plug and play” architectures, as the current ones used for automation in factories and offices are proving restrictive. Closed, proprietary systems need to embrace improved inter-operability and standards such as IEC 61499. The establishment in 2021 of the UniversalAutomation not-for profit as a global user organisation for a new automation paradigm is significant.
  2. Artificial Intelligence (AI) in every process: the challenge of staff absences during the pandemic has created renewed emphasis on AI and process automation. There is now widespread availability of large-scale pre-trained AI models for computer vision, text processing and more. For example, the Hugging Face site currently offers over 25,000 natural language processing models and clear examples on how to fine-tune them. In customer-facing processes, where question answering chatbots can dramatically improve productivity for common queries on shipments, etc, quality and speed of deployment is improving rapidly.
  3. Remote collaboration with intelligent automation, and virtual / augmented reality (VR/AR): as more intelligent devices and sensors are used in processes and factories, it becomes easier to interact remotely (for example, to offer assistance in repairing a machine, or completing a manual task in a warehouse). Digital twins of processes and equipment provide baselines for investigation and diagnosis of problems. Hence, the combination of digital twins, real-time information from processes and devices, and low cost VR and AR can transform the economics of remote site inspections, quality assurance and maintenance.

These trends support a broader trend to distributed workforces as we have experienced during pandemic lockdowns, i.e. a digital “anywhere” workforce. There are clear benefits in terms of real-estate footprint, and other cost efficiencies. However, there are obvious implications in terms of employment and working conditions as automation changes jobs and task profiles (or eliminates them).

Also, it is important to appreciate that more virtual ways of working changes on-going costs in areas such as IT infrastructure and higher-waged automation support teams, etc. Crafting the business case itself requires specialist knowledge of options and risks.

Our industry ranges from near fully-automated production lines for beverages and personal care products to the labour-intensive practices in some segments in apparel. Amongst other concerns, our industry is at the heart of societal dialog on the gender composition of the global workforce. 

Further success with automation in Consumer Goods won’t come from just following technical change. It requires compelling business cases, but it also demands sound judgements on our future role in society and industrial relations.

I’ll be talking about these topics and more at the upcoming End-to-End OpenSpace sessions, with the first being on 24th January.

And, to learn more about how issues are impacting CGF members and the Consumer Goods industry at large, take a look at the Global Summit 2021.