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Daikin Industries, Ltd. and Hitachi, Ltd. announced that they will embark on a collaborative creation aiming to establish a next-generation production model utilizing IoT in order to support skill transfer from expert workers.
Daikin will introduce a system that utilizes advanced image analysis and other technologies - the solution core of Hitachi's IoT platform "Lumada" - to enable digitalization, comparison, and analysis of the skills of expert workers and trainees. This is being done in the brazing process, part of the manufacturing process for air conditioners at Daikin's Shiga Plant at Kusatsu, Shiga Prefecture, and the objective is to ensure consistent quality, improving productivity, and developing human resources at production locations worldwide.
Daikin and Hitachi will jointly demonstrate the viability of a production model using this system, to begin full-scale operation of the system in actual manufacturing workplaces during this fiscal year, and aim to expand applications of the system to other Daikin factories and manufacturing processes worldwide. Starting from the joint demonstration experiment, Daikin and Hitachi plan to advance their collaborative creation towards the realization of a next-generation production model, in which global locations coordinate and share their information, skills and techniques utilizing advanced IoT.
Hitachi considered that it could provide support for the efficient skill transfer from expert workers to a large number of workers by advanced image analysis that detects signs of deviations of workers' motion in front-line and facilities failures to quantitatively digitalize, compare, and assess the skills of expert workers and trainees. Under the cooperation with Daikin, Hitachi has conducted validation tests for the digitalization and modelling of workers' motions and use of tools, etc., in brazing processes in the manufacture of air conditioners. By analyzing data gathered from brazing processes from the "4M" perspectives of "Man", "Machine", "Material" and "Method", Daikin and Hitachi considered the extent to which the data could be linked to the creation of new production methods. It has now reached a stage where there is potential for applying systems for the digitalization and modelling of workers' motions and other phenomena to actual manufacturing workplaces.
Based on validation tests conducted so far, Daikin and Hitachi constructed a Brazing Skills Training Support System that quantitatively assesses and analyzes differences in brazing work carried out by expert workers and trainees, and they are now set to introduce the system to the actual manufacturing workplace at Daikin's Shiga Plant, and to begin joint demonstration in October 2017.
Specifically, the system chronologically collects and digitalizes motion data-including hands of expert workers, torch angle and angular velocity, and the angle, distance and angular velocity at which the filler materials and workpieces are supplied-using cameras and sensors, and uses the data to construct standard motion models.
Similarly, by gathering and digitalizing data on movements and characteristic phenomena occurring when trainees carry out brazing work, the system makes statistical comparisons with the standard motion models created based on expert workers' motions. This enables quantitative assessments of the brazing work of trainees based on the examples set by expert workers, allowing trainees to acquire the necessary skills in a shorter period of time, and enabling the company to seek to standardize and improve upon worker's skill levels. This should lead to improved consistency of quality, increased productivity, and enhanced development of human resources working on the front lines of manufacturing worldwide.
Based on the results of these joint demonstration, by establishing unified standards for brazing work for introduction at all global production locations, and by integrating and analyzing data together with data from monitoring & control systems and production equipment, Daikin and Hitachi plan to further improve quality and productivity, and to train more skilled, expert workers.