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【2019 Application Example】 How can public restrooms rely on IoT and cloud technology to become cleaner, solve 70% of customer complaints, and increase efficiency by 120 times?

IoT smart restroom: A revolution of clean, power-saving, and convenient new smart restrooms

Six sensors are used to detect toilet paper, hand soap level, water leakage, odor, people flow, and toilet usage conditions, and combined with NBIoT transmission, cloud system, and LINE robot. It greatly reduces customer complaints and improves the efficiency of replenishing consumables in restrooms. Coupled with real-time notifications, it can prevent illegal smoking in restrooms and improve safety. Users will no longer face the dilemma of wet, dirty, smelly restrooms, or toilet paper running out, greatly upgrading their experience.

What is your impression when you walk into a public restroom in a popular tourist area? No hand soap? No toilet paper? Or even a dirty, smelly, and leaking restroom? The IoT big data smart restroom solution of the Institute for Information Technology (III) solves all inconveniences of restrooms all at once.

According to statistics of the Environmental Protection Administration (EPA), Executive Yuan, there were more than 43,000 public restrooms registered and managed in Taiwan as of the end of September 2019, but the entire EPA only had over 34,000 people. Cleaning and managing such a large number of sites is obviously not an easy task. Coupled with the inevitable arrival of an aging society, the number and quality of personnel cleaning restrooms will inevitably encounter unprecedented bottlenecks. The introduction of effective service processes and assistance of technologies has become a major issue that must be faced sooner or later.

The IoT smart restroom service solution demonstrated by the III at over 20 restrooms around Taiwan may provide a good direction for us to solve this problem.

Overwhelming number of customer complaints, four major problems, and three solutions of the III

In 2016, when the MRT Songshan Station, which is connected to the train station, was officially opened, the public restrooms that were already at full capacity resulted in serious customer complaints due to the overwhelming use. Songshan Train Station, which originally had an average daily passenger volume of only 40,000, was already near a bottleneck in service capacity. After the connected MRT Songshan Station was opened, the number of passengers increased to 70,000. The restrooms that were already near full capacity were completely unable to cope with the additional passenger volume after the MRT station was opened.

Cao Xueqin once wrote a classic line that touched people's hearts in the novel "A Dream of Red Mansions": "When a wall is about to collapse, everybody gives it a shove" may be able to describe this phenomenon: The toilet paper and hand soap in each restroom was never replenished in time, the sinks were dirty, and the toilets could never be cleaned in time. There was an overwhelming number of customer complaints about the restrooms as a result. In addition, the public restrooms of Songshan Train Station are closer to the main passageways of passengers than the public toilets of MRT Songshan Station. At this point Songshan Train Station had to face and solve this problem.

Since Songshan Train Station has worked with the III for a long period of time, it commissioned the III to help solve this troublesome problem.

Edison has a famous saying: "If I find 10,000 ways something won't work, I haven't failed. I am not discouraged, because every wrong attempt discarded is another step forward." The first thing that the III needs to do is conduct pain point analysis and think about the underlying problem. After reviewing customer complaints and discussing and analyzing them with front-line cleaning service companies, the III found four problems and three solutions:

The four problems are: Toilet paper and hand soap are not promptly replenished, sinks are damp, and the space has a foul smell.

The three solutions correspond to these four problems respectively: 1. Delicacy management of consumables such as toilet paper and hand soap. 2. Digitize the key performance indicators (KPI) in the service process, such as the dampness of the sink, or the odor concentration in the space. 3. Use new Internet of Things (IoT) technology to implement the first two solutions, and assist big data and cloud technology in achieving efficient site cleaning management.

"Technology features and R&D process"

The combination of six key sensors with IoT cloud motherboard and big data, thoroughly resolving 70% of customer complaints and increasing efficiency by 120 times.

I. Delicacy management of consumables

To achieve delicacy management of toilet paper and hand soap, the first step is to develop sensors to detect these two consumables.

Starting in 2017, the III began to design the first infrared toilet paper detection module. The module mainly uses the physical characteristics of toilet paper usage habits for detection: Under normal use, toilet paper is placed on an iron drum holder, and its thickness slowly becomes thinner as it is used.

This module requires the combination of a position sensitive detector (PSD ), infrared emitting diode (IRED), and signal processing circuit (SPC) to effectively determine the length of toilet paper with accuracy reaching one decimal place.

When the detection module was first developed, there were no designs that could be referenced, so sensor selection, circuit board designing and planning, sensor programming, and even the light-cured 3D printed casing design were all completed in the III.

Public restroom field detector demonstration image


However, despite overcoming all the difficulties in designing and producing the toilet paper sensor, there was no way to foresee that fixing the sensor in place would be the most difficult problem.

Public restroom sensor display picture


The III team shared with us: “At first, we used hot melt adhesive to fix it in place, but cleaning personnel needed to open and close it every time they replenished toilet paper. The sensor fell due to too much vibration and not being firmly fixed in place.

The worst situation was in the women's restroom: When a female passenger was using the toilet, the sensor was not properly fixed in place and fell. Don’t you think this sensor looks like a pinhole camera? If something like this suddenly falls on the ground in the women's toilet, how bad do you think it will be? (laughs)

Fortunately, our superiors supported us, and we continued to develop the technology until we were able to successfully fix the sensor firmly in place. Otherwise, this project would have been aborted a long time ago."

Sensor with line interactivity demonstration


After the toilet paper detection module was launched, an inspection of toilet paper usage that once took cleaning personnel 15-20 minutes to complete now only takes 10 seconds by opening the app. This greatly improved efficiency by 120 times.

Now that the consumption of toilet paper has been solved, the next problem is detection when hand soap is at a low level.

Unlike toilet paper, the amount refilled each time for hand soap isn't always the same. Because the design philosophy was to use the lowest cost and most stable components to complete this function to facilitate future scaling, a common Hall sensor was chosen. It was mounted on the exterior of the soap dispenser to achieve the detection of low soap levels.

The principle is actually very simple. Once the liquid level is lower than a certain percentage, the Hall effect sensor can sense the change in voltage from electromagnetic induction of the liquid level. The sensor sends a signal to the back-end cloud server, and then the server then sends a message to cleaning personnel the same as the toilet paper sensor.

II. Digitization of key performance indicators (KPIs) in service processes

If the sink is wet, water will often seep onto the floor. In addition, the bottom of passengers’shoes will inevitably carry dust, so the floor will become dirty when they step on the wet floor. Visually, this will give people a sense that the “restroom is dirty." However, it is impossible to have cleaning personnel on duty in the restroom at all times, so a special sensor is needed to detect this situation.

The III uses the resistance characteristics of thin film resistors. When there is liquid on the surface of the thin film resistor, it will lower the overall resistance value and further change related values of the analog signal output. In this way, moisture can be detected by simply laying thin film resistors on surfaces that often become wet. For example, next to the windowsill or on the sink.

However, since sensors are relatively expensive and scratches will damage the performance of the sensors, this moisture detection sensor is only used in specific public restrooms.

Apart from looking dirty, if a foul smell comes from a public restroom, people will think it is dirty even if it looks bright and clean.

However, odor detection is not that easy to solve.

At first, we searched all kinds of sensors in Taiwan and overseas to find this "electronic nose." We eventually found a suitable MEMS chip in the product line of a major Japanese manufacturer that specializes in the production of gas sensors.

The III started from breadboard testing, circuit design drawings, to outsourced chip production, taking nearly six months to complete the design of the sensor.

Furthermore, in the process of developing smart  restrooms, we also received requests to develop other modules, such as people flow detection and usage detection.

感測器配置於洗手台下方呈現


During the development process, we found that users may accidentally close the door of some accessible toilets after use and forget to turn off the lights, so it seems as if the toilet has been occupied all day long. However, people who really need to the toilets are blocked outside the door of accessible toilets that are actually vacant. This problem was relatively simple. The engineer found a ready-made people flow sensor module and installed it under the sink, and the problem was easily solved.

In addition, environmental protection and carbon reduction requirements are hard to meet for some remote public restrooms, such as Tri-Mountain (Lishan) National Scenic Area. Due to the remote location, responsible personnel must turn on the lights every day at work and turn off the lights when they get off work. Sometimes not many tourists use the public restroom all day long, but all the lights and equipment are still on all day long, which is a waste of electricity.

Generally, commercially available sensors are very dull and will turn off the power as soon as the set time of 30 seconds to 10 minutes is up. Such a sensor may be adequate at home when only one person uses the toilet. However, in a restroom that can easily reach 60 ping or above, several detectors will be needed to work together to ensure whether there are still users in the restroom. This is another problem without a commercially available solution. The III had no choice but to integrate multiple sensors and develop algorithms on the MCU to solve this problem.

III. The introduction of new IoT, cloud, big data, and 5G NBIoT technologies

On the path of innovation, there are always difficulties waiting for engineers to overcome. In the process of solving problems as they come, we also refined the solution step by step, making it cheaper, more reliable, and more convenient.

After the sensors described above were completed, the system gradually generated new problems for the III to solve. For example, the barrier of user habits, power consumption issues, cost issues, etc.

The app was changed to a LINE group robot to become more aligned with user habits

透過電信商、技術商、服務商擴散至場域的 Line 服務擴散系統圖

When the public restroom of about 60 ping at Songshan Train Station was completed for the first time in 2017, MCU and WIFI communication were used to monitor and transmit data to the server around the clock. After the system determines an abnormality, it uses the mobile app developed by the III to notify cleaning personnel.

This design seems to be impregnable at first glance. However, the average age of on-site cleaning personnel is over 50 years old, no one used the dedicated app, and front-line personnel often deleted the program within a few days of use. There is a whole set of sensors monitoring, but no cleaning personnel actually use it. User habits are often the biggest obstacle to the introduction of new technologies.

After conducting user interviews we found that the cleaning personnel of every public restroom have a LINE group.

廁所設備 LINE 群組溝通使用圖

The III team mentioned: "Knowing that they ( cleaning personnel ) have a LINE group makes things easier!

At first, we cautiously asked the cleaning personnel if they would invite a robot "new colleague" to help inspect toilet paper and determine abnormalities in the restrooms.

At the beginning, the cleaning ladies were a little skeptical. When they discovered that this robot "new colleague" was very useful, they fell in love with it."

Due to cost, environmental protection, and convenience issues, WIFI was upgraded to NBIoT communication protocol.

WIFI is fast and has wide bandwidth. A restroom has a men's room and women's room, which requires two separate systems for monitoring, and each system needs an independent 4G network to connect to the cloud system. Therefore, the construction and communication costs are relatively high, and the power consumption is also relatively high.

At this point, readers may have questions: Public restrooms are all set up in public spaces. Is there no public WIFI network available?

The III team gave us a very in-depth answer: "Actually, almost every public space has a WIFI network that can be used. However, sharing WIFI with other people is prone to interference, and IoT devices are simple and lack security control mechanisms. If you use public WIFI, there is a certain degree of security. risk.

Therefore, in our solution, we still designed a closed WIFI communication system to solve the communication problem.

In addition, since a WIFI base station can only support 20-30 nodes, a women's room with 18 toilets requires a separate systems. Coupled with the fact that it is separated by a concrete wall, the signal will be very weak and even affect the stability of the signal. Therefore, a public restroom installing two systems is mainly due to stability considerations rather than cost considerations."

In densely populated areas, using WIFI to transmit data to the server is not too troublesome. However, when smart restroom systems are beginning to be applied to restrooms in remote areas, such as Lishan, Guguan, Shitoushan and other public restrooms of national park visitor centers, maintaining network connection is indeed a difficult problem.

Fortunately, new generation mobile communication networks of 5G includes narrow-band Internet of Things (NBIoT) specially designed for the Internet of Things. The III is the first in Taiwan to develop Taiwan's first NBIoT MCU control system designed for smart restrooms using the NBIoT chipset of a domestic chip manufacturer.

In addition to the significant cost reduction, this system is also very energy efficient, requiring only 1/6 of the power of the original WIFI system. The most important thing is that compared to traditional WIFI, which requires a relatively stable 4G signal connection, this system has wider coverage and allows communication deep in the mountains and out in the wild. This allows wider coverage of smart restrooms in the future without being limited by network signals.

IV. "Effect Analysis and Future Outlook"

IoT smart toilet: A revolution of clean, power-saving, and convenient new smart toilets!

As the complete set of sensors, cloud system, NBIoT, and LINE robot are gradually launched, the benefits are clear.

In the case of public restrooms at Songshan Train Station, from being overwhelmed at first to greatly reducing the number of customer complaints by 70%, the time required to inspect toilet paper use was shortened from the original 15-20 minutes to only 10 seconds. Once an abnormal situation occurs, it has gone from being undetected to the prompt notifications today.

Interestingly and unexpectedly, this entire system also brings the added benefits of safety and thorough enforcement of tobacco hazards prevention laws. When a toilet is occupied for more than 40 minutes, a warning will be sent to the cleaning personnel group. Hence, when a user occupies a toilet for too long, cleaning personnel will knock on the door. This greatly improves safety.

In addition, odor detectors are also very sensitive to the smell of smoke. Since smoking is prohibited in national parks, tourists sometimes sneak into public restrooms in remote areas to smoke. In public restrooms of national parks, once the odor detector detects the smell of smoke, it will play a voice message about the Tobacco Hazard Prevention Act to let tourists clearly know that smoking in public restrooms will result in a fine of NT$2,000 to NT$10,000. Since the installation of odor detectors, the number of users smoking secretly in public restrooms has significantly decreased.

The "smart public restrooms" at Songshan Train Station won the "Golden Way Award" from the Ministry of Transportation and Communications for overcoming various difficulties, which made it famous. From a constant stream of customer complaints to model public restrooms that the public sector has enthusiastically visited, the additional workload on the case officer from handling group visits is actually a luxury to be worrying about.

Future Outlook

The system has proven its stability and cost effectiveness during the three years of R&D and field experiments, and has now been successfully transferred to domestic system integration companies. The III also hopes that this system can be expanded in the future, and the technology can even be transferred to Europe and the United States.

In addition, on the basis of stable and reliable data flow and communication connections, the introduction of big data for analysis may make the deployment of manpower more delicate, and the problem of uneven work distribution can be expected to be fundamentally corrected.

Facing the arrival of an aging society, NBIoT communication systems, combined with various IoT sensors, may be able to bring us a healthier and safer living environment. Some repetitive tasks that traditionally relied heavily on manpower can also use technology to greatly improve efficiency.

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【導入案例】防患於未然 麗臺科技研發心臟衰竭AI辨識技術可及早發現病徵
Preventing Problems Before They Arise: Leadtek Research Develops AI Technology for Early Detection of Heart Failure Symptoms

With the increase in the elderly population, the incidence of various chronic diseases is rising daily Among these, heart failure is not only a silent killer it has a very long disease course with a high recurrence rate, leading to increased burden on healthcare personnel However, by using medically certified electrocardiography acoustics devices, coupled with AI predictive assessment of heart failure risk and remote care systems, diagnosis can be aided significantly, helping doctors make accurate diagnoses for subsequent patient medical care or referrals Heart failure has a lengthy course and medical expenditure is five times that of diabetes If you find yourself short of breath even with minimal movement, or if you wake up from sleep needing to sit up to feel comfortable, or if you have symptoms such as swollen lower limbs, anxiety, restlessness, fatigue, or a loss of appetite, be cautious These could be signs of heart failure According to statistics, there are about 60 million people with heart failure worldwide, with 5 million new cases every year In China, nearly 290 million people suffer from cardiovascular diseases, accounting for the second leading cause of death among urban residents around 12 million of these are heart failure patients, accounting for over 59 of cardiac-related deaths The disease course of heart failure is exceptionally long, and both its recurrence and rehospitalization rates are exceedingly high, resulting in medical costs that are twice that of hypertension and five times those of diabetes According to US research statistics, the 30-day mortality rates for patients with myocardial infarction and heart failure are respectively 166 and 111, and the rehospitalization rates within 30 days are 199 and 244 The symptoms of heart failure, because they are similar to those of other diseases such as chronic obstructive pulmonary disease and asthma, have an 185 misdiagnosis rate, which poses a challenging problem for healthcare institutions Leadtek, a major graphics card manufacturer, has been investing in the medical and healthcare sector since 2000 Following two heart attacks in 2011 and 2015 experienced by Chairman Lu Kunshan, Leadtek has focused on health big data, independently developing AI technology for heart failure recognition This AI application reads patients' electrocardiograms and phonocardiograms to perform anomaly detection and model prediction of heart failure risk, enabling early detection of disease symptoms Leadtek independently developed heart failure AI recognition technology to predict medical history and risk Leadtek's independently developed heart failure AI recognition technology has the following three judgment functions 1 Prediction of heart failure history Classifies electrocardiogram and phonocardiogram data into 'with hospitalization history of heart failure' and 'no history of heart failure' 2 Risk prediction of heart failure Provides a predictive risk value of heart failure occurrence based on the electrocardiogram and phonocardiogram data 3 Prediction of heart failure recurrence risk For patients with heart failure, it reads their phonocardiogram and electrocardiogram data, assessing the risk prediction of heart failure recurrence Leadtek states that the application of heart failure AI recognition technology can assist doctors in making more efficient and accurate diagnoses, facilitating subsequent medical treatment or referrals for patients As an instance, in studies of heart failure patients discharged from Taipei Veterans General Hospital, using the EMAT Electromechanical Activation Time index and SDI Systolic Dysfunction Index calculated by the synchronized electrocardiography-acoustic device as treatment guidelines resulted in a higher survival rate compared to those treated based on traditional symptoms This research has also been published in the authoritative international cardiology journal JACC, receiving recognition in the international market System manufacturers can apply heart failure AI recognition technology for other value-added applications Leadtek states that cooperating system manufacturers can choose to build their own heart failure AI risk prediction engine, uploading their system's electrocardiogram and phonocardiogram data to Leadtek's heart failure AI risk prediction engine, which then returns risk prediction values for integration by system manufacturers cooperating manufacturers as a value-added application input Not just for clinical use, the heart failure AI risk prediction engine can also be extended for use at home or in the workplace Additionally, this system can be extended to other applications, including One, hospital outpatient screening Doctors can use the electrocardiogram and phonocardiogram recorder along with the heart failure AI risk prediction model to conduct a 10-second rapid test in outpatient and emergency departments to assess a patient's cardiac history and heart failure risk Two, discharge risk assessment Doctors can use the electrocardiogram and phonocardiogram recorder along with the heart failure AI risk prediction model to assess the heart failure risk during a patient's hospital stay The test data can serve as a pre-discharge risk assessment and prognostic indicator Three, continuous home care Patients can use the electrocardiogram and phonocardiogram recorder, wearable electrocardiogram recorder, and transmit through a home transmission box gateway to measure electrocardiogram and phonocardiogram signals at home and upload them to the amor health cloud platform for heart failure AI risk prediction analysis Patients can manage their health autonomously via an APP, reviewing historical physiological trends disease management nurses can manage member health through the health management backend Web Four, home rehabilitation training Patients can wear a health bracelet to monitor activity, fatigue, circulation, and sleep, autonomously managing their health through the mobile APP and observing the risk of heart failure, engaging in exercise and rehabilitation training to aid in swift recovery The heart failure AI recognition technology system can also be extended to employee home care applications Additionally, in factories or offices, this system can also achieve employee health management goals, with applications including One, workplace safety units Provide employees with wearable electrocardiogram recorders before they start work duties Two, physiological monitoring for business executors While executing business duties or training, employees wear wearable electrocardiogram recorders for fatigue warnings, signaling whether physiological conditions allow continued execution of tasks Task segments can use data transmission boxes or apps to upload physiological monitoring information to the health management platform, assessing the heart failure risk for operations staff, with test data serving as an indicator for enterprise resource human units and public safety Three, workplace physiological monitoring center care The workplace physiological monitoring center can inspect and record employees' historicalphysiological trends through the health cloud platform Four, workplace nursing units Nursing units receiving instructions from the physiological monitoring center can provide health management advice based on employees' physiological trends nursing centers can manage employee health through the health management backend Web Five, employees can wear health bracelets to monitor activity, fatigue, circulation, and sleep, autonomously managing their health and observing the risk of heart failure through the mobile APP, engaging in exercise and rehabilitation training to aid in rapid recovery Workplace application of heart failure cloud care and big data center diagram「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

這是一張圖片。 This is a picture.
CCTV Intelligent Video Search System

Search for a specific person, find someone with a suitcase entering the factory in Gao'an area Color features of the person and the object confirmed, person in blue and black top, suitcase in black color, throughCCTV the intelligent video search system, by setting object and color retrieval conditions, it can successfully locate three video clips containing the target subject This greatly aids operational staff in finding the target items, and through this system, search speed can far surpass manual effort6fold Pain Points The CSE-Kaohsiung Plant is densely equippedCCTVto monitor every corner of the plant area, but when an incidenthappens, it's impossible within a limited time throughCCTVvideo playback to find the incident, the implications and risks behind this are self-evident Many areas that are usually unmanned can easily become security blind spots Thus, how to monitor a vast plant area more intelligently and effectively is one of the crucial aspects of building a smart plant for the semiconductor industry The AES Plant in Kaohsiung covers a vast area, with many important sites requiring monitoring of personnel movements to ensure corporate secrets and employee safety 1 Automated production lines and warehouses In semiconductor enterprises’ automated production lines and warehouses, oftenAGV(Automated Guided VehicleAGVs automated guided vehicles travel at high speeds if plant personnel inadvertently enterAGVthe moving area and cannot issue a warning to the person, then the regrettable accidents that occur will be too late to reverse 2 Material and product storage areas Materials used in semiconductor-related processes are costly if areas storing materials or products are breached, there is a risk of loss of high-value materialsproducts 3 High-security areas Trade secrets relate to the core technological competitiveness of semiconductor-related enterprises if someone breaches the high-security areas, there is a risk of corporate secrets being leaked The safety of trade secrets has always been one of the most critical issues for semiconductor enterprises 4 Loading docks At AESLButthe dock area often has loading vehicles coming and going if someone intrudes into the dock area, there is a risk of vehicle collisions and accidents Additionally, goods awaiting shipment at the dock area could be stolen or potentially damaged from collisions, thus causing significant reputation and financial losses for the company, further leading to production and shipping inconvenience When an abnormal event occurs, how to quickly search for the relevant key footage from massive data Many important locations within the AES Kaohsiung Plant need to be equippedCCTVfor safety checks, butCCTVWith thousands to tens of thousands of cameras, manually searching through footage for an event requires laborious frame-by-frame review which is time-consuming and inefficient In light of advancements in computer vision, it's beneficial to utilizeAIto replace manual playback and searching Problem Scenario Object Detection The data source for object detection comprises two parts Open-source datasetsOIDv4and AES Kaohsiung PlantCCTVImage files For these files, search for usable data, specificallyOIDv4image files For these files, extract the defined nine major categories of objects for training data among them, two object categories, knives and gasoline barrels, were not found inOIDv4found usable data for knives and gasoline barrels, while the remaining seven categories of objects are available fromOIDv4useful training data found for the remaining seven categories of objects, all marked Regarding the Kaohsiung PlantCCTVimage files, select some frames Frame of the footage, and manually annotate the objects to be_detected for training and testing data Nine Major Objects Color Recognition The data source for color recognition is divided into two partsInternet image screenshots, and Kaohsiung PlantCCTVimage files Currently, no publicly available open-source datasets specifically for color recognition applications have been found, so images are collected from the web Search the web for images of the defined nine major object categories, save the images after separating the objects from the background, keeping only the object sections, and mark the images according to color Additionally, for the Kaohsiung PlantCCTVimage files, use the already-markedbounding boxextractCCTVimage files from variousFramesections of objects identified by color, and finally, visually identifiable images are marked according to color Each object category has its specific color definition, depending on the usual colors seen in these objects in real life Dynamic Ignore during Training FromOIDv4during the training of the object detection pilot model, since each image in this dataset is only marked for a single category, but the image may contain other desired detection categories unmarked For such cases, dynamic ignore techniques will be employed during training to avoid 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Translation date:2024-12-12」

這是一張圖片。 This is a picture.
AI-Based PCBA Surface Defect Detection Improvements

With the introduction of theAOIAIWith the introduction of the system, we can improve product yield, reduce costs, and from a business perspective, increase customer trust and sales revenue Moreover, AIit has advantages that are difficult to imitate, unlike other equipment that can be bought with money, making it hard for our competitors to catch up with us Our company's current development We are committed toIOTsmart manufacturing our systems already include smart materials systems, environmental humidity control systems, anti-miscarriage systems, smart procurement computation systems, smart inventory systems, solder paste management systems, and production management systems We have asked other manufacturers about the possibility ofAIinspectingPCBAsurface defects, each hoping that we would purchase their equipment, but none were effective upon verification After discussing with IT service providers, we defined it asAOIAIa feasible operational model Tzuhong Technology has invested inAOIAIan inspection plan to checkSMTtext on components, solder joints, polarity, missing partsand usingAIto replace manual learningAOIand define the 'potentially defective' parts, enhancing productivity and reducing misjudgment rates Industry pain points Taiwan faces a severe labor shortage, especially those willing to perform visual inspections are few and typically older, increasing the frequency of missed inspections Thus, the most critical bottleneck in the pursuit of high-quality electronics has become post-production inspections Previous consumer products with undetected anomalies were acceptable within a certain ratio However, in the automotive industry today, undetected defects could lead to fatalities hence, the automotive industry has extremely high quality demands To survive in the automotive supply chain, we must address the issue of undetectable anomalies Moreover, as wages in Taiwan continue to rise, we can only endeavor toAIreplace traditional manpower with technology, otherwise, even if the anomaly leakage problem is resolved, the relatively high labor costs will still prevent competitiveness in this industry Application technology and explanation Initially,Figure 1,PCBUpon emerging,Reflowsystem, it will undergoAOIwill undergo inspection, dividing into 'suspected defective' and good products At this point, the 'suspected defective' portion accounts for20manual review for these20parts, further classifying the 'suspected defective' portion into good and defective products With We aim to leverageAItechnology, to shift from manual re-inspection of these20technology, we aim to replace manual review of 'suspected defective' products withAIand after review, the results still yield 'good' and 'suspected defective' products, but now 'suspected defective' comprises only3thus reducing the workload of Tzuhong's employees from20down to only3In theory, it isAOIIn theory, after inspection, it is further reviewed byAIbut it appears to go throughAOIonly, so we call this technologyA0IAIDetectionFigure 2。 The original AOI inspection process The operator will place the testPCBboard intoAOIthe inspection equipment, outputtingAOI information on defective products, then manually re-inspect one by one to determine if they are defective AOIAI inspection process The operator will place the testPCBboard intoAOIthe inspection equipment, outputtingAOIinformation on defective products after, then proceed byAIfirst performingAOIre-assessment of defective products, outputtingAIinformation on defective products afterward, then manually re-inspect one by one to determine if they are defective Process differences By introducing theAOIAIsystem, not only can we enhance the efficiency and yield of visual inspection personnel, we also have this timeAIexperience in system introduction, we will also incorporateAIthe use of big data into Tzuhong's existing smart manufacturing systems, further enhancing the performance of our smart manufacturing systems and reducing the pressure on employees Difference between pre and post-introduction Promotion strategy 1 Similar field diffusion allSMTmanufacturers face bottlenecks in inspections leading to shipment delays introducing this system can solve the severe labor shortage issue and enhance shipment speed and quality, allowing self-promotion to customers or through equipment dealers to cater to relevant needs 2 Cross-industry expansion plans negotiate withAOImanufacturers to directly integrateAIthe system intoAOItheir systems, enhancing their market competitiveness Profit strategy 1 In collaboration withAOImanufacturers, collect licensing fees 2 Direct sales toSMTthe manufacturing industryAIsystems 3 ProvideSMTmanufacturing industryAOIAIsystem subscription model「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-09」