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Control Plan using AI

Omnex integrates Artificial Intelligence (AI) into its Quality Management Systems (QMS) to enhance the creation and management of Control Plans. By leveraging AI, the Omnex system can automatically suggest control characteristics, measurement methods, and control methods based on historical data, DFMEAs, and process flows. This reduces manual effort, improves accuracy, and ensures alignment with APQP requirements.<br><br>AI also enables real-time monitoring and predictive insights, helping identify potential failures early. Integration with digital PFMEAs, process flows, and real-time shop-floor dat

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Control Plan using AI

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  1. Get updates DIGITALIZATION OF QUALITY SQM.AI EQMS.AI SQM.AI    SQM.AI SQM.AI SQM.AI Revolutionizing Supplier Quality management using AI Welcome to SQM.AI, where cutting-edge artificial intelligence transforms supplier management and elevates performance. Our comprehensive software platform centralizes supplier information, including metrics, PPAPs, APQPs, audits, receiving inspections, and SCARs. Utilizing advanced machine learning, deep learning, and natural language processing (NLP), Omnex BOTs (O-BOTs) meticulously review PPAP documents to ensure unparalleled accuracy and efficiency. By implementing the Plan-Do-Check-Act (PDCA) cycle, our system fosters continuous improvement with AI-driven automation.

  2. Effortless Supplier Onboarding and Management Onboarding suppliers is simplified with AI-based sentiment analysis. Our Project Review OBOT tracks suppliers for New Product Introduction (NPI/APQP) or PPAP around the clock, offering real-time insights and reviews. Maximize ROI in Your Supply Chain Identify and manage the bottom 20% of suppliers for quality, delivery, or service effortlessly with SQM.AI. Our BOTs help pinpoint areas for improvement and track progress effectively.

  3. Flexible Deployment and Expert Support Available both in the cloud and on-premises, our intuitive interface simplifies complex tasks. Benefit from global implementation services and expert e-learning resources to optimize and standardize your processes, empowering superior supply chain performance. Feature Highlights AI/ML PPAP Reviews Ensures high-quality and timely PPAP submissions Snapshot Project Reviews Available anytime, providing continuous oversight Root Cause Analysis AI identifies quality issues by analyzing data patterns and correlations Audit Guidance AI guides auditors, provides real-time feedback, documents findings accurately, and automates trend analysis

  4. Savings 95% 50% 76% Reduce Risk Reduce Cost Maximize Value

  5. Benefits of Artificial Intelligence Strategic Advantage Accelerate product launches Data Insights Gain valuable insights from your data Supply Chain Excellence Drive superior performance Risk and Rework Reduction Minimize risks and reworks Answers to AI FAQs 01 01 01 What key features does the platform offer? Key features include supplier management and onboarding, documentation management, APQP/PPAP submissions, supplier audits, SCAR management, receiving inspections, and AI-driven insights through Omnex BOTs (O-BOTs). 02 02 02 How does SQM.AI enhance the platform’s functionality? SQM.AI, machine learning, and deep learning algorithms meticulously review PPAP documents. NLP further

  6. automates and streamlines the evaluation process. 03 03 03 Can the platform integrate with existing business systems? The platform integrates seamlessly with existing ERP, CRM, and other business systems, enhancing data flow and process efficiency. 04 04 04 How can I start using the platform? Contact us for a demo or consultation. Our team will guide you through onboarding, including setup and integration with your current systems. 05 05 05 Is the platform available in both cloud and on-premise versions? Yes, the platform is both a cloud-based solution and an on-premise installation to meet diverse business needs. 06 06 06 What kind of support is available for new users? We offer comprehensive support, including documentation, tutorials, webinars, and a customer support team available via email and chat. 07 07 07 How accurate does the SQM.AI make the predictions in the QMS? The accuracy of SQM.AI predictions depends on the quality and quantity of the data used for training the models. Continuous training and validation of the AI models using up-to-date and diverse datasets (70-30 rule) help improve accuracy. When an inaccurate prediction is identified, Human experts (Human in the Loop - HITL) review and train. The system learns from the mistake, adjusting the model parameters to improve future predictions. Omnex Subject Matter Experts (SME) will validate and train the model with your historical corrected data, and subsequently, this will be transferred to your organization's experts. Company Software Platform About Omnex Systems NPI/APQP

  7. Our Values Electric & Autonomous Vehicle Executive Team Quality Management Systems / QHSE (IMS) Become a Partner Supplier Quality Management Client List Performance Management Worldwide Offices Manufacturing Digitalization 4.0 (I-IoT) Awards and Accreditations Products Products AQuA Pro DFMEA, PFMEA, Control Plan development, and PPAP Documents Requirements Flowdown Requirements Management Functional Safety Functional Safety Software Document Pro Document Management Software Change Management Change Request Management APQP/PPAP Manager NPI/APQP Project Management Inspection Control Inspections Management Audit Pro Audit Management Software BOSS Continual Improvement & KPI Management Layered Process Audit (LPA) Layered Process Audits Problem Solver Internal & External Customer complaints HR Pro Training & Competency Management MSA Pro Gage Management and MSA Studies software TPM Pro Total Productive Maintenance Management Request for Callback Newsletter +1 734-585-1369 Be the first one to know about our Training, Webinars, Product release information and insights +86-21-33608488 +91 95000 74866 Sign up for our newsletter +49 17 89888 121 +49 17 89888 121 +49 17 89888 121

  8. © 2024 Omnex Inc. USA. All rights reserved    Questions or comments regarding this website: webmaster@omnex.com Privacy Policy Terms of Use

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