The Research Centre for Human-Collaboration (HUMAC), led by Professor Dr Yap Kian Meng, together with the members of HUMAC, Associate Professor Dr Lee Yun Li, and Associate Professor Dr Lin Mei-Hua have completed and delivered the prototype for the real-time counting application of printed circuit boards assembly (PCBA) to Deng Kai Sdn. Bhd. under Public-Private Research Network (PPRN) 2.0 Grant.

This project aims to solve the main issue of monitoring the production output in Deng Kai Sdn. Bhd., which specialises in the manufacturing of engineering components. Currently, affordable solutions for small and medium-sized enterprises (SMEs) to monitor production data in real-time that directly affects the operations of the company remain a major challenge. For instance, the average output is capped at a certain amount which is far from the production capacity of the factory. Due to the lack of online monitoring solutions, the company cannot analyse and determine real-time production output data. Besides, employees’ tasks of counting components manually, frequent breaks, motivation, and morale affected productivity.

Hence, to address these issues, a prototype Internet-of-Things (IoT) weighing scale system and a vision-based counting system were developed to monitor the production outputs in real-time. Subsequently, a reward system was introduced to encourage the employees. The IoT weighing scale was developed with Arduino, sensors, and self-designed 3D printed materials, whereas, the vision-based counting system was developed with the Raspberry Pi and USB camera. Both systems pass data to the cloud database powered by Amazon Web Service (AWS) to support the real-time monitoring of production output via the proposed Android mobile application. A simple user interface design of the Android mobile application provides managers to easily conduct monitoring of production output in real time.

Furthermore, the usability observations for both proposed systems and Android mobile applications were carried out among the operators and managers in the company during software development iterations to meet the real-time environment process requirement. A reward system for the workers was also developed in tandem with the company’s direction. A reward system that sets a daily or monthly target rather than individual and team reward was recommended to overcome the challenges of daily changes in the composition of the work teams. It was also recommended that additional recognition in form of a certificate of good attendance could be awarded to the employees to boost workers' motivation, morale, and productivity.

The reward system fosters healthy competition between teams. The IoT weighing scale and vision-based counting systems motivate the teams to speed up the production process, and any delay or breakdown be identified and addressed within a short period. Therefore, this project has increased production efficiency. This real-time monitoring system could increase revenue by identifying the causes of the delay. Furthermore, with the automated monitoring, weighing scale, or counting solutions, the company has freed up the low-level skills of staffing, who perform the tasks manually, and created higher-level job opportunities.

Upon completion of the PPRN 2.0 project, Deng Kai Sdn. Bhd. the Director, Mr Lian has agreed to continue supporting the project as part of HUMAC and the Department of Computing and Information Systems (DCIS) for the final year industry project on vision-based inspection of PCBA quality using machine learning techniques. This creates opportunities for DCIS students to solve real-world problems and possibly explore career opportunities within potential industries.  

Figure: Prototype of IoT applications for monitoring production output in real-time: (a) IOT Weighing Scale System, (b) Vision-based Counting System

Associate Professor Dr Lee Yun Li 
School of Engineering and Technology
Email: [email protected]