How AI is Changing the Face of Operations Management
Rapidly evolving technology is transforming every field, and manufacturing is no exception. Once a crude, blue-collard work environment with manual processes, it has today become the centre of innovation and machine intelligence. Artificial intelligence techniques are the key to unlock value and optimize processes in this field.
Cost pressures are rising as industries get increasingly competitive. Heavy industries like chemical, power, and thermal, with longer gestation times and long-term ROI, are facing the brunt, not only from within but also from the fast-moving external factors. For example, labour which was once readily and cheaply available, is now hard to get.
We see robots and automation coming to the rescue, a better alternative than uprooting manufacturing facilities to low-cost locations. Also, manufacturing trends in itself are changing, made-to-order is the new way. Just-in-time, lean manufacturing calls for lesser inventories and a more real-time operations environment. How, then do manufacturers adopt and embrace this shifting scenario? The answer lies in becoming smarter and better through artificial intelligence.
Artificial intelligence or machine learning is an approach of using massive data sets to train machines to perform tasks in semi-supervised ways. This applies to the entire life cycle of manufacturing right from problem identification to problem communication and then resolution. Automation is necessary to streamline repetitive tasks such as scheduling and rescheduling, planning and data tracking.
Thus, following are the two critical roles played by AI:
- Predictive analysis of various data points to pre-empt anomalies in operations / functions .This can go a long way in bringing to notice aberrations and thereby avert critical catastrophes! Such AI-enabled systems must be instilled for material, machine and equipment updates and also extend to the systems that they interactive with such as customer orders and supply-procurement.
- Automate routine decisions, freeing up personnel bandwidth. As a result of outsourcing the mundane to ‘smart’ machines, personnel can focus on more value-adding tasks and the unit can function optimally with lesser personnel.
- AI should touch all aspects of the production value chain, right from the shop floor to management systems and resource deployment systems.
The field is making fast progress towards disrupting the manufacturing domain. We have come a long way from the first time AI was introduced when in 1965. Dr Herbert Simon, one of the founders of artificial intelligence (AI) said, “Machines will be capable in 20 years of doing any work a man can do.”
Today, MIT economists Erik Brynjolfsson and Andrew McAfee have argued that technology has replaced jobs in America at a faster pace than creating the new ones. Many organizations are already lapping up the AI-revolution, in a recent example, Foxcann, the No.1 EMS in electronic industry. They were planning to deploy over 10,000 robots to factories in an effort to offset the pressure of increasing labour cost in China. High margins in hi-tech manufacturing is the fuel for companies, both large and big, to change their strategies.
The bottom-line for such changes is to stay relevant in the market and provide the best product and services in the market, at the best price. If that means, doodling with data and experimenting with artificial intelligence, the industry is all up for it.
