kunstig intelligens for business

Digital employees for manufacturing industries just make sense

During my talks and sales meetings, I have frequently used the analogy of the automation of blue-collar jobs in factories using robots to how we are transforming offices and white-collar jobs through digital employees.

After a recent chat with Saraswati Jituri, my colleague who has a long background in lean for the manufacturing industry, we find that the manufacturing industry is very mature to receive digital employees to automate their back-office tasks as well.

The main reason is simply that the manufacturing industry is already in the correct mindset, they had been through the transformation using robotics once and had seen the impact of automation, they had dealt with the risk of adoption among the employees, and had reaped the benefit of production increase through automation. So, for them, the learning curve is much smoother than for other industries who are facing the potential for automation for the first time.

Though the majority of the work is located on the production floor where robots are already striving and producing daily, there is enough work in other departments that needs help through what AI can produce.

Due to the complexity of manufacturing, tasks such as supply chain, quality control, and HSE are still being done manually. Digital employees can take care of employee’s tasks, whose job is the registration of incidents, fill in and copy information to ERP system or other relevant back-office systems, and to generate reports for the different internal and governmental needs.

To ensure the production speed, ensuring the stock level of raw material and parts is important. Requests may be coming in from different factories and vendors with available parts may be spread across the globe. When to order from whom at what price would become crucial, ordering ahead with a larger volume often will give discounts. Because of this complexity, procurement and supply chain management is often done manually and are often time-consuming.

Given today’s technology, most of the decision making and vendor selection can be done automatically and integrating with the procurement management system. Effectively removing the time needed to operate on the different systems and the time it takes to create and recreate RFQs and POs.

The quality of production defines the quality of the product, to avoid costly recalls (for cars, and for other large machinery), each step of the production is closely monitored, and each mistake is to be learned to avoid making it again. There are a lot of logs, reports, defects, quality issues that are registered manually in ERP systems and its supporting systems. The data remain in the system are difficult to refer back and get insight due to the volume and the way it is organized. Imagine a digital employee who can register, analyze, categorize, and archive each of such logs and reports in a structural manner and can retrieve it whenever it is needed, completely automated. Furthermore, such a system can also analyze the cause of defects given the relevant data is recorded as well. This will not only improve efficiency in working with quality control, but also improving the quality of production as well.

HSE (Health, Safety, and Environment) is a headache for many project managers. In Norway, the requirements are set to be very high and it is often a burden for the resources in terms of incident registration and reporting. Information remains in the system after the reporting is done but due to the unstructured nature of the incident logs, it would be difficult to make use of the information to prevent future incidents.

Imagine a digital employee who can register analyze, categorize on the incidents in an organized way in the system,

and build the need report for governance, and in addition, can use the data in an efficient manner to prevent future incidents, an organization could save the administrative cost on HSE and at the same time become proactive in reporting and prevent incidents.

Digital employee from Simplifai is applied into a wide area of use cases, any tasks that start with incoming text in the form of email or document will be efficiently categorized, information extracted, and be registered to the ERP system or other relevant back-office systems.

The whole process is automated using our solution modules built with our core AI technology and are connected together using our standard robotic architecture. Such a project lasts 3 to 4 months from specification to delivery, so one can have a digital employee working quicker than a traditional recruitment process.


Erik Leung, Chief Operating Officer