AI is not just for use by large-scale industrial enterprises; it can also make tangible differences to smaller sized businesses looking to optimise operations. Production lines, warehousing, logistics, and even complex ‘pick and pack’ processes are some of the typical operations where even small-scale introduction of AI technologies can mean significant benefits. Effective deployments of AI in these areas can quickly build competitiveness and help future-proof operations.

Some of the AI technologies that can add intelligence, insight, and real-world learning benefits, include:

Data Mining - This is the process of sorting through large data sets to identify patterns and relationships to help solve business problems through data analysis. For example, using machine learning to mine through data gathered during a manufacturing process, it could be possible to spot recurring issues or understand what conditions might be happening that could lead to sub-standard manufactured parts, such as wear in a mould, die, blade, or tool. These insights could be extremely valuable to preventative maintenance planning, quality control, and operational planning.

Image processing technology – This is a way of presenting processed data in a way that can give a more useful visual form to make determinations from. Sometimes it can even help show things that might otherwise be “invisible” to the human eye. For example, object identification and segmentation on a busy ‘pick and pack’ process can augment production efficiencies by spotting multiple object types through pixel imaging and supplying the insight to best handle these objects. It also may be able to spot anomalies or foreign objects.

Image enhancement by way of noise reduction, enhanced colour, super resolution and increased dynamic range also assists with object tracking improvements, including the identification of where a particular object on a production line spends most of its time.

Image processing AI technologies help operations make more informed decisions since it allows them to continuously learn, and in turn optimise performance. This can result in better product routing, scheduling and layout improvements, and provide quantifiable solutions for companies competing in an increasingly competitive marketplace.

In summary, AI has the capacity to help decision makers gain a deeper understanding of their responsibilities, whether it be manufacturing, quality, operations, or even analysing trends in certain markets. This can help business leaders effectively plan and execute overall business strategy, automate complex operations, and adapt to changing market conditions, all while continuing to execute their strategic goals. The AI appeal is democratic no matter the company size and ultimate corporate ambition. It is important to start small and seek to build AI investment in tandem with system experts who can oversee and guide the implementation, so key performance indicators are clearly set, are achievable, and deliver the bottom line results desired.