Outcomes , Insights and Best Practices from IIC Testbeds : MQM Testbed
authorization ) cost by improving the manufacturing quality . The reason this approach was chosen was because the feedback loop required for fine-tuning at this stage of the process did not exist . In the initial phase , the focus was on how certain platforms can help , especially on the analytical engines described in the IIRA .
One key factor contributing to the MQM Testbed ’ s success was paying careful attention to the specific challenge chosen by the client for the testbed to address ; in this case , making improvements to the false detection rate on the failed products of the production line was an issue the client cared about and was willing to work to improve . Haier , in spite of hearing all of the hype about how IoT process can help them , had never tried to act on it due to the risk of disrupting their existing manufacturing process . Despite an initial level of skepticism and even resistance to IoT concepts , the MQM Testbed was so successful that Haier now wants to create an internal branch to renovate all of their production processes . Originally , the focus of this testbed was on one of Haier ’ s air-conditioner production lines . Then , because the results were so successful , Haier agreed to expand the MQM Testbed to a second line - kitchen vents .
CHALLENGES
Many factors affect production line quality in factories . The challenge faced in the air conditioning production line is that centered on a welding station where the cooling tubes at the heat exchanger are connected . The heat exchanger is the most crucial part of the air-conditioner and the most difficult part to be detected should there be a leak caused by the welding process . Initially , the first goal was to improve efficiency of the welding process and eliminate any point of failures .
However , trouble immediately arose because the team discovered it was almost impossible to add sensors and a controller to the old welding robots of the welding station .
Due to high temperatures and the intensive sparks generated during welding , the testbed team found it impossible to apply any kind of sensor into the welding station unless the sensor was pre-installed on the welding robot . The team reported this problem in one of the regular testbed updates during one of IIC ’ s quarterly meetings and solicited help from other IIC members . FujiFilm and Olympus who both have experience and solutions in welding quality control , came forward to help and offered their solutions through thermal imaging . However , the solutions offered are good for post-welding quality check and the team found , again , that the solutions cannot be integrated easily with the existing system . The clock was ticking and the chance to find a quick solution was running out .
Since an immediate solution was not available , the team decided to seek an alternative solution . The first step was to reexamine the whole production process and see if there were other angles to be used . The initial approach focused on the production side of the production line and was deemed impractical . The team decided to take a field trip and get familiar with the actual production line . The focus had been on the production station , but the team felt there is something in the process they had possibly overlooked , especially on the quality control process . When the engineering team arrived at the factory , they soon discovered that the quality control process was very primitive and there was a lot of room for improvement .
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