The manufacturing sector has more experience of significant non-human involvement in its research, operations and administration than almost any other after decades using data analysis, machine learning and robotics. Now AI is being used to harness the power of these well-established methods to reshape traditional manufacturing processes. This is ushering the industry into a new era of intelligent automation in pursuit of optimising efficiency and prompting still greater innovation.
According to research conducted by Make UK and Infor published in November 2023, more than half of manufacturing companies (55%) have already implemented, or are planning to implement, AI and Machine Learning to automate decision making processes and improve operational efficiency.
As with most examples of widespread and fundamental change, there will be pluses as well as minuses from the increasing application of AI.
Benefits of AI in manufacturing
Improved operational productivity and efficiency
Intelligent automation systems powered by AI algorithms will optimise production processes, streamline supply chain management and should minimise routine downtime. Predictive maintenance will also facilitate proactive rather than reactive identification of problems developing with equipment and potential failures, reducing unplanned repair and replacement downtime and the consequential reduction of output.
Huge amounts of data can be analysed in real time by AI algorithms, allowing the identification of patterns and anomalies which might otherwise go undiscovered. AI systems can leverage machine learning techniques to learn continuously from data inputs, adapt to changing conditions, thereby making data-driven decisions to maximise the output from manufacturing processes.
Robotics and AI are creating more efficient and flexible autonomous systems
Robotics and AI are coming together to set up new generations of autonomous systems, which are transforming the manufacturing environment. Robots using AI capabilities are able to operate collaboratively with human workers and perform increasing complex tasks with unparalleled precision, speed and consistency. This is cutting the manual labour component in the process and raising production efficiencies.
Changing manufacturing systems in response to changing production demands can be a costly and resource-intensive experience. Bringing robotics and AI together can facilitate the development of more flexible manufacturing processes capable of reacting more efficiently to such changes. AI-enabled intelligent robots can be reprogrammed to carry out different activities far more quickly, which gives manufacturers the flexibility to reconfigure production lines to meet new product demands, reduce their time-to-market and potentially gain vital competitive advantages.
Data-driven decision making and predictive analytics
Huge amounts of data are generated by the proliferation of sensors and connected devices in manufacturing environments. AI can harness the potential of this data to give manufacturers real-time insights and invaluable predictive analytics. Its algorithms can effortlessly analyse both structured and unstructured data, gaining insights into innumerable key issues within manufacturing operations. These may include demand forecasting, leading supply chain management improvements and inventory optimisation.
Redeployment of skilled labour resources to more sophisticated tasks
AI systems can undertake more mundane and repetitive actions, allowing skilled human resources to be reassigned to higher-level problem-solving and decision-making activities. Human/machine collaboration is becoming increasingly common in manufacturing settings, with staff inter-acting with AI driven-systems through applications such as voice commands or wearable devices. This allows employees to access real-time information and to receive AI-generated recommendations.
Downsides of AI for manufacturers
Labour force issues
AI-enhanced intelligent automation is likely to eliminate some lower-skill jobs and increase job dissatisfaction for some retained staff. There will be a constant need to invest and re-invest in upskilling the work force.
Data privacy and security concerns
AI relies heavily on data collection, analysis and storage. Inevitably, this creates issues regarding security and privacy of sensitive data, as well as with compliance with UK and international regulatory requirements. Breaches or unauthorised access to such data can result in intellectual property theft, compromised trade secrets and the risk of regulatory sanctions.
Creating a single point of failure
Excessive reliance on AI systems for critical manufacturing processes can easily create the classic manufacturing nightmare – a single point of failure, where any malfunction causes production delays, downtime and financial losses without any scope for an effective Plan B.
Technical challenges of implementing AI in manufacturing
Introducing AI-driven applications into existing manufacturing systems is inevitably complex. It needs major technical expertise to ensure sufficiently robust processes, with acceptable levels of reliability, accuracy and safety. Challenges can arise with data integration, system inter-operability and bias in algorithms.
Implementation costs
Bringing in AI technology is bound to cause significant upfront and ongoing costs for infrastructure upgrades, training and ongoing maintenance.
Ethical issues of AI
Ethical concerns are legion, covering aspects such as transparency, fairness, accountability, and the potential for AI models to reinforce existing bias or discrimination.
The exclusion of human experience and intuition
Whatever benefits AI systems bring by way of hugely enhanced data analysis capabilities and automation, they generally mean the elimination of human experience, judgment and intuition. It is vital that it remains possible for human intervention to deal with some complex decision-making requirements, particularly in those scenarios in which unforeseen circumstances or non-routine events occur.
Staying up with and in control of AI in manufacturing
AI has developed at extraordinary speed and continues to accelerate. Tools are upgraded, updated or replaced with bewildering frequency. Capabilities and their dangers planned for and recognised one moment are old hat almost before companies can implement them.
Manufacturers must have robust AI strategies, including comprehensive data security measures, ethical guidelines, employee training programs and contingency plans to address potential disruptions. Falling short on these essential safeguards risks losing control of technology that has become an integral part of a business’s operations. Approaching the integration of AI technology carefully and with futureproofing in mind will set manufacturing business up well in the long-term.
If you are seeking professional advice for your business, Opus is here to help. You can speak to one of our Partners who can discuss options with you. We have offices nationwide and by contacting us on 020 3326 6454, you will be able to get immediate assistance from our Partner-led team.