Key to bridging the gap between the next revolution relies in the data you already own in order to take full advantage of Industry 4.0, according to Jason Chester of InfinityQS.
As a buzzword, Industry 4.0 or ‘4IR,’ is becoming more and more mainstream – a quick Google search will prove testament to this. In essence, it is the embodiment of the smart factory concept, with machines that are highly interconnected through the internet and are part of a real-time ecosystem that can visualise, and optimise, the entire supply chain.
Moreover, entities throughout the system can make their own decisions based on artificial intelligence (AI) or support human decision making processes through advanced analytics and visualisation through augmented, and even virtual, realities.
For manufacturers, large and small, the business case for embracing Industry 4.0 is enchanting. Efficiency, scalability, agility are again enticing buzzwords that reinforce why so many are keen to jump on the 4IR wagon. But scratch beneath the surface and is this desire translating into action?
Recent research from The Manufacturer’s Annual Manufacturing Report conducted extensive research into how well firms are embracing Industry 4.0. The findings made for interesting reading:
- 67% of UK manufacturers recognise Industry 4.0 as an opportunity
- However, only 25% of firms feel they have an adequate understanding of the opportunities and challenges surrounding Industry 4.0
- Arguably the most telling concern held by business was their lack of appropriate expertise to exploit the opportunities of Industry 4.0 (52 per cent)
Given our reliance on technology, many might question why manufacturing, such a formative industry, is so under developed and unable to capitalise on this new industrial revolution? It might seem obvious, but the simple answer lies in the fact that a lot of the practices and approaches employed by manufacturers are still built on the processes and procedures used in Industry 3.0 and, to a lesser extent, Industry 2.0, to use a comparative vernacular.
Arguably, the clearest demonstration for this argument can be seen in how manufacturers practice quality management today.
Quality management typically conjures up images of statistical process control methodologies used to study how a process changes over time—the main driver for which is to use these insights to reduce waste, inefficiency, recalls and ensure compliance standards are met.
For many manufacturers however, the tools of the trade for managing and monitoring quality control are often nothing more than a pencil, a paper form and a clipboard. If there is a failure in your ‘technology,’ a pencil-sharpener is often the remedy.
Information is noted onto worksheets, and then gathered together across multiple sites and plants. This information is then bundled together and lumped into a spreadsheet to sit and gather dust in a filing cabinet, or at best siloed in databases or file servers across the organisation.
When you consider the power that data possesses today, the idea of ignoring it seems incomprehensible. Indeed, it could be argued that just as oil powered the growth of the industrial economy in the 20th century, data is the new oil that will power the industrial economy through the 21st century.
Used effectively, data from the manufacturing plant, and across the supply chain, can provide strategic operational insights to help drive continuous transformation in quality, processes, and overall operations. For many manufacturers often governed by legacy practices, they simply can’t imagine that this same information they’ve held all along is able to unlock dramatic improvements in yield, compliance, and resource utilisation. Leveraging cloud computing is a way to change this.
By thinking in this way, manufacturers can begin to achieve an aggregated, end-to-end view of production sites across the entire enterprise and create a foundation for digital transformation to support their Industry 4.0 aspirations.
Benefiting from the resulting insights, firms are able to develop a continuous cycle of real-time improvement that gives them an edge on the competition. This sees the formation of an ‘excellence loop,’ which consists of three interconnected parts:
- Enterprise Visibility: When all quality-related data is unified from all sources into a standardised and centralised repository, it’s possible to visualise more than the quality of a single production line. The outcome is real-time visibility of the entire enterprise, from end to end—including suppliers, incoming inspection, raw materials, in-process checks from shop floor operators and the quality lab, process data, packaging, and finished products.
- Operational Insight: With visibility of the entire operation, useful and actionable insight is generated about the enterprise’s processes, suppliers, and manufacturing operations. Improved analytics and reporting help to apply best practices consistently across all plants, lines, processes, and products in a prioritised manner.
- Global Transformation: Finally, the resulting insights can be applied to streamline, optimise, and transform processes and operations across the enterprise, elevating product quality, improving efficiency, and creating exponential cost savings.
This excellence loop demonstrates the true capabilities and scalability that can be gathered from embracing digital transformation, allowing a manufacturer to gain the most from their information.
The speed in which technology is moving and enabling us to better our business offerings means firms can no longer be resistant to change. For manufacturers, the reliance on legacy practices often associated with the second and third industrial revolutions means critical sources of information are being ignored, which is debilitating their ability to keep pace and meet future challenges head on.
Understanding and leveraging this information now, allows you to bridge the gap between previous information revolutions as well as equipping you with the tools to address the challenges of tomorrow.