Global Manufacturing is currently going through a technical revolution which has become known as “Industry 4.0”. There is increasing focus on smart factories and intelligent manufacturing systems that have a greater integration between the physical and digital processes, thus creating “Cyber Physical Systems”.
But, is industry 4.0 delivering on its promises?
Despite investment the industry is still seeing widespread issues, including:
- Outdated or unreachable technology
- Supply chain transparency and trust
- Unproductive centralised supply chains
- Non-conformance management
- Manufacturing process control
- Constrained capacity planning
- Lack of machine health monitoring
- Energy efficient use of assets
Although there are clearly advances for a manufacturing company that invests in Industry 4.0, research reveals that only 13% of companies are getting the value that they believe they should. Combining the relevant technologies is key to success and could translate to a £1.2 billion saving for the sector.
Industry 4.0 alone is not providing the benefits that it should be. Artificial Intelligence and Machine Learning can change that if applied in the correct way.
What can AI do for manufacturing?
The current state of manufacturing does not include automatic visual defect identification as part of the production line. As a result, defects aren’t detected until later on the process which is costly to the producer.
Vision systems are emerging that can check parts visually and assess it to the correct quality standards. By implementing this into a production cell, parts can be checked visually for conformity. A self-learning feedback system can then send information back to the machine to enable it to adapt.
Addressing the issues earlier in the process reduces scrap costs and increases productivity which both effect the bottom line. Visual inspection results can be combined to ensure that machine capability and quality is constantly improving and is not impacted by outside influences.
Any manufacturing process requires precision attention to detail, a necessity even though deadlines are shortening, products are becoming more complex and customers expect higher levels of service. As a result, manufacturing facilities are finding it increasingly harder to uphold quality levels and to comply with quality standards. Not fulfilling these requirements results in higher defect rates, which in turn leads to loss of profit and damage to your company brand.
Quality management systems in most factories today are controlled via manual processes. This requires a highly skilled engineer to ensure that components are being manufactured correctly and to specification, which is especially true in the defence and aerospace verticals. However, humans make mistakes and there is always a conflict between the goals of quality and production.
The application of AI technologies to the data that is being collected via Industry 4.0 sensors will ensure that quality systems and processes are adhered to at all times, regardless of whether there has been human input or not.
A major contributor to lost production and delivery failures is unplanned downtime. The Internet of things (IoT) has enabled factories to take a significant step towards controlling unplanned maintenance better, but AI technology will improve the situation further.
Currently an engineer can monitor the data being output to spot changes and make adjustments but what happens when the engineer has other commitments or while they aren’t at work?
AI can not only observe changes that a human couldn’t detect but can also watch the data 24/7. By monitoring the machine maintenance occurrence data, AI algorithms can be used to predict maintenance issues before they happen. This has the added benefit of freeing up engineers to carry out more value-added activities as well as machines don’t unexpectedly stop working.
Adjusting to ever-changing demand
For any manufacturer, under and over estimating demand leads to lost revenues and the largest inefficiency in any manufacturing supply chain is its failure to be flexible to global demand.
Industry 4.0 is seen as a key enabler with 9 out of 10 factories investing, however only 13%1 of them are seeing the benefits because a combination of emerging technologies is required to generate the full value impact. Unfortunately, many companies lack the resources to translate this information to reduce costs and increase efficiency. For that, companies will need to implement Artificial Intelligence.
Adding AI technology into Industry 4.0 applications will enhance supply chains and will help businesses foresee market changes.
With this technology enabled, the outlook of production leaders and executives will move from reactive to proactive. Such a factory system would allow optimisation of raw material orders, consumable requirements, inventory levels, energy optimisation and labour requirements.
One of the biggest costs for any manufacturing facility is its energy. Most factories operate 24 hours a day to achieve maximum availability and scheduling the more energy intensive activities for when energy costs are lower can lead to significant savings. For instance, if solar power is a source of power then daylight hours are the most ideal. Likewise, if solar isn’t available, lower electricity costs can be obtained during the night when demand is lower.
1 Source: Accenture Industry X.0 Combine and Conquer,
In reality, energy saving isn’t that simple. A considerable number of factors would need to be included to optimise energy usage effectively. Data such as the power usage of machine tools, cutting tools, materials, labour costs, solar power and power storage availability would all need to be calculated, which would overwhelm a human to the point that it wouldn’t be workable. However, this is a perfect use for Artificial Intelligence. AI algorithms would take a multitude of inputs from the factory and production systems and schedule the perfect time to complete energy intensive activities to realise the full cost savings.
Being able to understand a manufacturers energy use will be key to them identifying inefficiencies and opportunities for improvement throughout the factory manufacturing system.
AI is a huge opportunity for manufacturing in 2021
These are just a small sample of what could be achieved with AI and ML in the manufacturing sector. As more businesses discover the benefits of applying these technologies to their processes, more applications will emerge.
Companies that understood the potential of AI quickly, such as Amazon, Microsoft and Google, have far outperformed their peers and grown aggressively, mainly due to their superior capability to forecast and continuously adapt to changing conditions and to generate higher margins.
Artificial intelligence is a disruptive technology that has shown enormous benefits in other industries when applied to manual methods and human decision making, which makes it ideal for disrupting the manufacturing sector.
How Manufactory Will Save Manufacturing?
Manufacturing plants and factories around the world must rely on Blockchain, smart contract and IoT to meet the rising global demand and transform the way we order, control quality, manufacture and deliver components.
Blockchain and smart contract technology has the potential to radically disrupt the current manufacturing business model by enabling trust within the supply chains, streamlining processes and improving transactional security. But most of all it will digitise manufacturing data which can be utilised to increase the effectiveness of any manufacturing system.
Manufactory is combining these technologies into a single easy to use platform that is built by manufacturers, for manufacturers.