Smart manufacturing is a powerful disruptive force that can restructure the current competitive landscape and produce a new set of market leaders. A factory that uses intelligent, connected production equipment and devices allow for data-driven decision-making that enables efficiency and productivity throughput. Introducing the use of advanced analytics powered by AI/ML allows the factory systems’ maturity levels to progress from connected and intelligent to self-awareness and, ultimately, autonomous systems.

Development plans focused on digital technologies have now been integrated as an organic part of the business strategy. Keeping up with the trends, QAI has planned the road map to implement a thriving Smart Manufacturing Ecosystem in factories.

First of all, we come to the representation of the layers of automation within a typical factory, called the Process Manufacturing Pyramid.

Let’s start at the bottom, on the production floor. This layer, or field, comprises a wide variety of sensor devices and hardware. The higher layer is production line control which is one of the vital parts in manufacture. Finally, we get to the planning level of the pyramid. This, now, is my favorite level because it contains the management execution system (MES). The top layer, management, is built around your company ERP, which gives company decision-makers information from every level of the Pyramid. Whereas MES monitors and controls a single plant, ERP provides monitoring, reporting, and control for entire corporations.

In QAI, we develop applications and solutions in the MES layer that assist in tracking important metrics, creating technical drawings, finding abnormal cases of goods, etc.

To be more specific, the value chain that the MES level brings can be illustrated as below:

In this value chain, QAI provides products and technologies that meet Product Design and Product Manufacturing features:

  • akaCoga supports creating and managing drawings and technical designs with absolute accuracy. akaCoga has been bringing value in the field of design: cars, interiors, and electrical circuits. 
  • akaInspection is a solution to help customers optimize the product inspection process. Applying AI/ML provides a solution for detecting defective product patterns in the past and detecting new anomalies occurring in products. 
  • akaCam can be used to identify people in photos, video, or real-time with 100% customer satisfaction improved and up to 50% execution time reduced.

And many other applications/services/solutions applied RPA, OCR, NLP & Chatbot to optimize the production efficiency, reduce human errors and enhance the quality of life.

To improve the quality of the MES level, we have created a roadmap that assists in achieving the value chain this layer brings to a smart factory. 

In the following year, we will focus on boosting the performance of akaCoga and akaInspection and improving existing AI technologies such as Optical character recognition and object detection. In the long term, we will collect the missing pieces to get the three main factors of domain application & technology picture: Domain/predictive models – Reuse & Agility – Collaborative system. 

To sum up, becoming a smart factory is a journey and requires technological advancement to get the manufacturing industry through its adaptation. A QAI roadmap concept is proposed and discussed with strategies to advance application and technology which could assist a successful implementation and transformation into a smart factory.