AI and Automation in Manufacturing

Manufacturing is an area ripe for automation. Machines and software have been automating manufacturing processes for centuries and it is no different as software providers move development into the realm of cloud technology and Artificial Intelligence (AI). Ryan Pearcy, SB Digital Associate Partner shares his expertise by identifying trends in manufacturing automation and how AI is penetrating this space.

The importance of Automation

Automation in manufacturing is the use of software and machines to perform specific tasks without the need for human intervention. Traditionally this would be frequent, repetitive or dangerous tasks but has moved into the realms of predictive and subjective areas, allowing humans to review, rather than do. All of this is to increase efficiency, quality, safety and provide greater insights for decision making.

The squeeze on labour markets following covid and politically triggered supply chain disruptions has driven up the need for automation with the International Federation of Robotics noting a 30% year on year growth rate in the use of machines, be that physical or virtual, to streamline processes. The demand is there, but what can be delivered.

Types of Machine Automation

There are multiple ways to automate manufacturing processes, each using a different blend of software and hardware. Examples of these include:

Computer-Integrated Manufacturing (CIM) – CIM is where the process is automated by machines. Robotic production lines are an example of this where prototypes, build, quality control, storage, data and distribution are automated.

Industrial Internet of Things (IIoT) – Devices connect sensors to triggers and use AI to automate actions and decision making based on pre-set parameters. These are effective feedback loops to improve precision and quality, but can also be used to trigger the start and stop of processes.

Hard Automation – This would be considered simpler automation where machines are programmed for a particular task.

Flexible automation – This builds on hard automation but allows for refinements to systems and processes via computer controls but with human intervention.

Software Automation

As well as the use of software for machines, cloud technology has advanced the development of back-office functions to streamline manufacturing processes further. This can range from a connected finance system to automate processing of transactions, to inventory management, delivery and forecasting.

Interconnected finance systems have been the norm for larger enterprises through the use of ERPs. These systems connect various elements of the business operations together into a single system where data can be shared but are expensive and therefore prohibitive for smaller businesses who have had to resort to manually transferring information from one place to another. The advent of cloud systems with secure API connections enables the creation of a “Modern ERP” which is tailored to the specific needs of the business but at a price point that is manageable. This plug and play style also enable businesses to grow and evolve without the pain of completely changing how a business operates. Data can be collected and shared through the systems removing manual data entry and enabling team members to be approvers and reviewers rather than processors.

Forecasting and demand planning is where AI comes into its element. By using big data and predictive analysis software uses historic trends, customer buying patterns, seasonality impacts, marketing plans and economic conditions to predict sales forecasts. Working backwards and considering resource availability also enables manufacturing forecasts to be automated. What was once the realm of Mystic Meg has become a science with increasing accuracy. Heavily used by the likes of Amazon these tools are starting to appear in smaller business systems and enable those that invest in technology to get insights that can drive business success.

Advances in inventory management enable automated procurement processing based on minimum stock levels. Combine this with predictive sales and production forecasting as discussed above and businesses can ensure they have lean inventory levels, reducing their exposure and the impact on cashflow.

Automated delivery tracking updates the system for where goods are located and reduces the need to chase suppliers and logistics partners and update customers as well as prompting communication where necessary. This can also update inventory levels automatically as status change through the process, which links into the automation on inventory management.

What’s next?

Automation continues to be built into manufacturing products, focussed around connected systems and triggers. Generative AI, such as ChatGPT, is still being built into software products and we would expect that to be the next big phase of automation development, changing how teams interact with the various systems they use.

As Chris George points out in his article regarding Research & Development tax relief, in some cases claims for additional tax relief can be applicable to companies who develop their own bespoke software.  However, utilising existing ‘off the shelf’ software and integrating it into your company’s operations is unlikely to breach the threshold to qualify as development.

As systems develop it is critical that business owners are aware of the possibilities and options available to them. We always advise speaking to an expert to ensure you select the right system for your needs, get this implemented correctly and have someone to reach out to for support if things change. The SB Digital team can assist so please reach out to Ryan if you have any queries by calling 0330 058 6559 or by emailing hello@scruttonbland.co.uk.