Time consuming in checking tens of thousands of control items

• Lacking suitable SPC systems for big facilities to contol massive control items in a rapid manner.
• Spending a great deal of time on plotting control charts instead of identifying root causes of anomalies.

A User-Certered SPC System

• With rich user experience, TYNE provides the quick view mode, enhancing efficiency in anomaly treatment.
• Automatic scheduling regulerly produces reports, simplifying the whole process.

Daily repetitive tasks wear the passion and energy of employees the most. A good tool not only enhances production capacity or yield rates, but also wins back employees’ hearts.

Multiple individual systems, information can only be passed manually.

• There are comprehensive information systems but the information is not connected nor shared.
• Abnormal batch can only be held manually or notified persons responsible, resulting in slow response.

The non-packaged SPC, system allows customization for data uploads.

• The system is developed by TYNE and SPC information can be transferred to other systems based on data survey.
• For instance, if SPC Rules are violated, feedback will be sent to Hold Lot System or the warning level of Alarm Server.

Abnormal data in SPC System is sent to other relevant systems to speed up message transfer, reduce manmade mistakes, and further enhance the level of automation within the factory.

Advanced analytical unable to be satisfied

• Anomalies can be detected, but causes and treatments cannot be collected for further analysis.

Anomaly reason analysis and other advanced analyses provided

• A summary report is provided collecting reasons with the higest frequency.
• Stratification analysis is provided to clarify the occurance of anomalies in different layers.

Only when anomalies are analyzed can factors from all aspects be effectively controlled. An SPC system should be not only anomaly monitoring, but also anomaly prevention.

Contol charts, however detailed they are, do not tell the overview of the whole facility.

• Unable to know the facility overview through checking control charts: a comprehensive perspective is lacking.

Dashboard provides a quick view of facility anomalies.

• My Dashboard and Monitor Board, designed specifically for management, allow users to grasp information of the whole facility within the shortest period of time.
• Monitor the status of the facility in real time through mobile devices, realizing mobile management.

Information of the whole facility can be obtained from a unified platform. Employees can follow the steps and put more effort into improving quality and exceeding client expectations.

Low Accuracy in Manually-Copied Data

• Wrong data may be entered when transferring from hardcopy to electronic files; or data may be hard to be identified because of illegible handwriting.
• Low data accuracy results in anomalies unable to be detected and seriously incorrect analysis.
• Monitoring or analysis is unable to be carried out because necessary data is missing.

Best Goalkeeper of Data Accuracy

• Data accuracy is the prerequisite of analysis. With a variety of fool-proof mechanisms or scroll-down lists, warning can be issued at the time of key-in for users to modify data, reducing human negligence.
• Ensure data accuracy and maintain data consistency throughout work stations.

Employees are the most valuable assets of a company. Optimizing operation reduces error rates, standardizes data collection and organization process, and enhances the confidence of employees.

Not understanding the values of data

• Control charts from the old system can only differentiate product types and measurement parameters; massive information is hidden .
• Although the purpose of anomaly control and detection is achieved, identifying causes of anomalies is still inconvenient.

Increase the value of the system with the assistance of professional teams in implementation.

• During the project implementation period, TYNE helps with the establishment of clear control layers and secondary information.
• With a more comprehensive collection of data, SPC makes follow-up analysis and issue identification easier.
• The system makes internal management and external client response easier and more efficient.

Shortened time in problem clarification leads to higher work efficiency. With improved efficiency, employees can put more effort into improving quality and exceeding client expectations.

Unable to analyze anomalies and actions in the past

• Without a professional SPC system, causes of anomalies and actions are oftentimes not fully collected.
• Unshared information results in personnel unable to be informed in real time regarding anomaly status.

Provide anomaly reason analysis and other advanced analyses

• Anomaly causes and treatments can be marked on the control charts so that all personnel can access the current handling status to avoid rework or delay.
• Provide analytical reports of all aspcets for a quick review of the reasons with the higest frequency.
• Stratification analysis compares differences among factors.

Only when anomalies are analyzed can factors from all aspects be effectively controlled. An SPC system should be not only anomaly monitoring, but also anomaly prevention.

High turnover rates of professionals make quality control unsustainable.

• With the lack of quality control professionals, relevant skills and experience can only be passed on through apprenticeship.
• Low automation leads to highly repetitive work, which furture results in high turnover rates.

Best Practice of Comprehensive Product Quality Control

• Users can edit their preferences to streamline the steps of operation and improve efficiency when conducting daily and repetitive analytical work.
• Personalized work lists can be shared to increase the overall efficiency of the department and save system resources.
• The system makes experience pass-on and information exchange easier.

The intelligent platform allows information, knowledge, and experience to be continuously accumulated, collected, and advanced for maximum knowledge management.

Each department has its own charts and reports, resulting in multiple systems within one factory.

• • SPC charts are oftentimes defined by individual departments via Excel spreadsheets. Files are scattered all over the place.
• • Information are not shared nor exchanged across departments. Data collection is incomplete in preprocessing, making it harder for information to be connected to data during postprocessing.
• • It is time consuming to identify abnormal batches, resulting in slow response to clients and losing the trust of clients.

A unified internal information platform makes data sharing much easier.

• Provide factory-wide shared data platform.
• The interface can be set with high flexibility, allowing data collection throughout the manufacturing process (incoming quality control (IQC), input process quality control (IPQC), and output quality control (OQC), just to name a few).
• A platform that connects seamlessly the whole quality control analytical process and organizes information, bringing maximum benefits to quality improvement and process optimization.

With a unified platform, massive amounts of data can all be collected without missouts, greatly reducing paperwork and accelerating information exchange.

Low Accuracy in Manually-Copied Data

• Wrong data may be entered when transferring from hardcopy to electronic files; or data may be hard to identified because of illegible handwriting.
• Low data accuracy results in anomalies unable to be detected and seriously wronged analysis.
• Monitoring or analysis is unable to be carried out because necessary data is missing.

Best Goalkeeper of Data Accuracy

• Data accuracy is the prerequisite of analysis. With a variety of fool-proof mechanisms or scroll-down lists, warning can be issued at the time of key-in for users to modify data, reducing human negligence.
• Ensure data accuracy and maintain data consistency throughout work stations.

Optimizing the mode of operation reduces error rates, standardizes data collection and organization process, and enhances the confidence of employees.

Lacking of timeliness in anomaly determination results in excess manufacturing costs.

• Unsmooth data collection and unprofessional SPC system leads to ill determination of SPC Rules.
• Control charts are only plotted once a day and oftentimes it is too late to identify process deviations, missing out on early action-taking opportunities and causing extra manufacturing costs.

Automated quality control index monitoring identifies anomalies in real time.

• SPC Rules are determined at the time of data entry. Anomalies are automatically notified to persons responsible for early action-taking.
• Anomaly reasons and actions are documented to ensure that everyone can access the latest information and all anomalies are properly dealt with.

Only when anomalies are analyzed can factors from all aspects be effectively controlled. An SPC system should be not only anomaly monitoring, but also anomaly prevention.

High turnover rates of professionals make quality control unsustainable.

• With the lack of quality control professionals, relevant skills and experience can only be passed on through apprenticeship.
• Low automation leads to highly repetitive work, which furture results in high turnover rates.

Best Practice of Comprehensive Product Quality Control

• • Users can edit their preferences to streamline the steps of operation and improve efficiency when conducting daily and repetitive analytical work.
• • Personalized work lists can be shared to increase the overall efficiency of the department and save system resources.
• • The system makes experience pass-on and information exchange easier.

The smart platform allows information, knowledge, and experience to be continuously accumulate, collected, and advanced for maximum knowledge management.

Each department has its own charts and reports, resulting in multiple systems within one facility.

• SPC charts are oftentimes defined by individual departments via Excel spreadsheets. Files are scattered all over the place.
• Information are not shared nor exchanged across departments. Data collection is incomplete in preprocessing, making it harder for information to be connected to data during postprocessing.
• It is time consuming to identify abnormal batches, resulting in slow response to clients and losing the trust of clients.

A unified internal information platform makes data sharing much easier.

• Provide facility-wide shared data platform.
• The interface can be set with high flexibility, allowing data collection throughout the manufacturing process (incoming quality control (IQC), input process quality control (IPQC), and output quality control (OQC), just to name a few).
• A platform that connects seamlessly the whole quality control analytical process and organizes information, bringing maximum benefits to quality improvement and process optimization.

With a unified platform, massive amounts of data can all be collected without missouts, greatly reducing paperwork and accelerating information exchange.

Low Accuracy in Manually-Copied Data

• Wrong data may be entered when transferring from hardcopy to electronic files; or data may be hard to identified because of illegible handwriting.
• Low data accuracy results in anomalies unable to be detected and seriously wronged analysis.
• Monitoring or analysis is unable to be carried out because necessary data is missing.

Best Goalkeeper of Data Accuracy

• Data accuracy is the prerequisite of analysis. With a variety of fool-proof mechanisms or scroll-down lists, warning can be issued at the time of key-in for users to modify data, reducing human negligence.
• Ensure data accuracy and maintain data consistency throughout work stations.

The mode of operation is optimized, which reduces error rates, standardizes data collection and organization process, and enhances the confidence of employees, beneficial for the health of employees both physically and mentally.

Monitoring cannot be carried out in real time, leading to excess manufacturing costs.

• Unsmooth data collection and unprofessional SPC system leads to ill determination of SPC Rules.
• Control charts are only plotted once a day and oftentimes it is too late to identify process deviations, missing out on early treatment opportunities and causing extra manufacturing costs.

Automated quality control monitoring shortens anomaly handling time.

• SPC Rules are determined at the time of data entry. Anomalies are automatically notified to persons responsible for early action-taking.
• Engineers can edit their preferences to streamline the steps of operation and improve efficiency when conducting daily and repetitive analytical work.

Only when the level of automation is increased can engineers have more time on anomaly treatment and prevention. They can also be more dedicated to quality improvement and exceeding the expectations of clients. With a professional SPC system, they can be at ease when facing clients’ inspections and gain the trust of clients.

makes machine comparison difficult

• Only fixed and limited SPC charts can be plotted via Excel.
• If spacial charts regarding individual machines or materials need to be plotted, additional manual work need to be put in to collect and organize data.

Provides daily SPC and advanced analyses

• With rich user experience, TYNE provides SPC functions easy to be carried out along with advanced analysis functions.
• Provides grouped charting regarding different control layers such as machines and materials.
• Provide root cause analysis report, allowing post-treatment data to be analyzed.

Without a full understanding of production equipment, capacity cannot be effectively estimated. With the implementation of SPC, yields of machines can be monitoring, trends can be identified to build a clearer understanding of machine performances, and stable machines can be fully utilized for capacity enhancement.