Busting Misconceptions Over AI In Manufacturing

Mike Loughran Mike Loughran
March 23, 2021 AI & Machine Learning

AI has a ‘mind of its own’

Artificial intelligence is the development of computer systems enabled to perform tasks which requires human intelligence. For example, machine learning is a subset of AI. Machine learning requires human data scientists to prepare the data, determine appropriate datasets and continually update the software with new knowledge and data so it can adapt. This data needs context and domain expertise applied to it before it is analysed to deliver valuable business insights.

Machines are pre-set and supervised by humans; it’s important to remember that they do not have consciousness. Of course, there are machine learning algorithms which gives the impression that they are able to learn on their own, but these are still controlled by engineers and will continue to do so for the foreseeable future.

AI will replace jobs

The most common fear when speaking about embracing robotic automation is the idea machines will replace jobs. There is no doubt emerging technologies will change future workplace processes, but it should be used in a way where it adds value. For instance, AI could help with more admin tasks enabling workers to handle situations that require judgement and creative thinking. In this scenario, workers are not replaced, but they are reskilled to oversee or manage AI systems.

Technologies such as AI will also create new career opportunities for the future workforce. The World Economic Forum (WEF) reported that there will be 133 million emerging roles globally by 2022 in its “The Future of Jobs 2018” report. This means there will be an increasing demand for data analysts and scientists, machine learning specialists and software developers amongst other occupations within the technology sector. Therefore, AI will help reskill the existing workforce and upskill the future generations.

AI is an unnecessary luxury

When traditional factory workers think of AI it is usually associated with glossy, state of the art robots. Due to the aesthetic and investment involved in embracing automation it causes some manufacturers to think it is indeed a luxury item which isn’t necessary especially when dealing with uncertain economic conditions as a result of the pandemic.

However, when you consider the need for manufacturers to improve customer interactions, generate revenue and analyse data to make faster decisions, there is an obvious necessity to increase productivity to grow the UK manufacturing sector and gain a competitive edge.

The work undertaken for the Made Smarter Review found that if UK manufacturers adopted Industrial Digital Technologies it would increase manufacturing sector growth between 1.5 – 3 percent per annum and create an estimated net gain of 175,000 jobs throughout the economy. Again, this ties back to the point made about AI creating opportunities and this will help SME’s capitalise on the opportunities of new technologies.

AI isn’t suitable to my business model

Producers of low volume or bespoke processes usually question the suitability of technologies such as artificial intelligence and robotics as they think it is too complicated for their existing production facility. There are many uses for AI in manufacturing such as: quality checks, predictive maintenance, generative design, customer service, digital twins, risk management and price forecasts.

Ultimately, AI will shorten design time and reduce materials wasted whilst improving productivity, and that is applicable for all manufacturing processes. AI is already transforming manufacturing in many ways. According to McKinsey, AI-based predictive maintenance typically generates a 10% reduction in annual maintenance costs and increases productivity up to 25%[1]. And so, it is proving to be an essential tool for future growth in industry.

However, another challenge is manufacturers understanding how scalable cloud computing enables modern manufacturing execution systems. Outdated IT infrastructure is a contributing factor holding back manufacturing companies from digitally transforming their production process. With cloud-based systems manufacturers can keep up with new developments as they are able to adapt to the need for more powerful capabilities.

At the enterprise level, cloud computing will impact how companies manage their operations, from enterprise resource planning (ERP) and financial management to data analytics and workforce training. Providers such as Microsoft Azure support open-source AI solutions such as those provided by Rockwell Automation with a focus on integration between cloud and locally hosted application components.

The next steps

In order to start embracing AI companies must carefully create a comprehensive strategy. This requires firms to organise their data, establish clear data protection processes and practices and set expectations on the outcomes. It will also entail some additional thought for the required tools to enable control and process engineers to understand analytic data.

Once that has been conducted, there is no reason why even the ‘unsuitable’ or ‘difficult to automate’ processes requiring flexibility cannot be resolved using artificial intelligence. The adoption of AI and other emerging technologies will gradually create powerful collaborations between humans and machines to increase productivity, leading to a stronger and more adaptable UK manufacturing industry.

This article was originally published in The Engineer.

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