List of IBM Predictive Maintenance and Quality (PMQ) Customers
IBM
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$67.5B
Since 2010, our global team of researchers has been studying IBM Predictive Maintenance and Quality (PMQ) customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased IBM Predictive Maintenance and Quality (PMQ) for Quality Management from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using IBM Predictive Maintenance and Quality (PMQ) for Quality Management include: NVIDIA, a United States based Manufacturing organisation with 36000 employees and revenues of $130.50 billion, United States Army, a United States based Government organisation with 453551 employees and revenues of $65.25 billion, Faurecia, a France based Automotive organisation with 150000 employees and revenues of $27.90 billion, Sears Home Improvement Prods, a United States based Professional Services organisation with 10 employees and revenues of $2.0 million and many others.
Contact us if you need a completed and verified list of companies using IBM Predictive Maintenance and Quality (PMQ), including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Faurecia | Automotive | 150000 | $27.9B | France | IBM | IBM Predictive Maintenance and Quality (PMQ) | Quality Management | 2017 | n/a |
In 2017, Faurecia deployed IBM Predictive Maintenance and Quality (PMQ) as part of a Quality Management initiative across its manufacturing footprint in France. The implementation focused on manufacturing quality and asset productivity, positioning IBM Predictive Maintenance and Quality (PMQ) to ingest and analyze machine and product-quality data for operational use.
The implementation connected PMQ to an IBM Cloud data lake to capture telemetry and production quality records, enabling data ingestion pipelines and analytics workflows consistent with predictive maintenance and quality management use cases. Functional capabilities implemented included predictive maintenance model training and scoring, anomaly detection for quality events, and centralized quality data aggregation to support root cause analysis and production monitoring.
Operational coverage targeted Faurecia manufacturing lines in France, centralizing machine and product-quality data for manufacturing operations, quality engineering, and maintenance teams. Integrations were explicitly centered on the IBM Cloud data lake, which served as the analytic repository and source for model development and quality reporting.
Governance and rollout prioritized manufacturing quality and asset productivity, aligning PMQ outputs with quality control and maintenance planning processes. IBM stated IBM Predictive Maintenance and Quality (PMQ) would enable better predictive maintenance models and reduce scrap and non-quality rates.
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NVIDIA | Manufacturing | 36000 | $130.5B | United States | IBM | IBM Predictive Maintenance and Quality (PMQ) | Quality Management | 2018 | n/a |
In 2018, NVIDIA implemented IBM Predictive Maintenance and Quality to support Quality Management in its chip manufacturing operations. The engagement delivered a highly available and scalable enterprise AI and machine learning platform for chip fabrication, with multiple models deployed to production, and an explicit estimate of annual cost reduction of $8M while maintaining manufacturing quality.
The implementation included onboarding new products into IBM Predictive Maintenance and Quality, working closely with engineering to build classification models, execute testing and validation cycles, and perform production deployment of those models. Parallel work with enterprise PTC Windchill PLM applied application upgrades and configurations, and produced deliverables such as BOM comparison tools, Design History Files, Automated Revision Sync up, a PLM Data Mart, PLM reports, and external contract manufacturer BOM packages to improve engineering efficiency.
Integrations were executed across the manufacturing stack, including PLM bill of materials synchronization with SAP ERP and ERP integration services that exchanged contract manufacturer planning, commitment, and inventory data to improve demand and supply planning and build execution collaboration. The program also supported Product Information Delivery systems for customer download of drivers and content, and incorporated enterprise security by integrating IT systems into an Enterprise Password Vault and applying security best practices. Business intelligence and operational visibility were enabled through BI reports built with Tableau, SQL, Splunk, and Excel.
Governance and operationalization emphasized close collaboration with engineering for requirements gathering, design, implementation, and validation of customizations, and established automated revision synchronization and PLM data governance patterns to control configuration and lifecycle data flows. IBM Predictive Maintenance and Quality was positioned as the core Quality Management application for predictive classification and operational monitoring, with production model rollouts coordinated alongside PLM and ERP integrations to align quality analytics with manufacturing and supply chain processes.
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Sears Home Improvement Prods | Professional Services | 10 | $2M | United States | IBM | IBM Predictive Maintenance and Quality (PMQ) | Quality Management | 2016 | n/a |
In 2016, Sears Home Improvement Prods implemented IBM Predictive Maintenance and Quality (PMQ) on IBM Cloud to analyze appliance telemetry and service logs. The deployment targeted service operations in the United States and was scoped to support field technicians and parts identification to improve service quality. Sears Home Improvement Prods deployed IBM Predictive Maintenance and Quality (PMQ) for Quality Management to support field service and parts-identification workflows and to centralize telemetry-driven quality controls. The implementation configured telemetry ingestion and service log analytics modules within IBM Predictive Maintenance and Quality, leveraging predictive analytics and anomaly detection capabilities typical of the Quality Management category to surface probable failures and candidate spare parts. The solution connected appliance telemetry streams and historical service logs to cloud-hosted analytics on IBM Cloud, enabling automated identification of required parts and diagnostic guidance for field technicians. Operational coverage focused on field service and quality management functions across the United States, with governance aligned to service operations and parts-identification processes. Per IBM's 2017 announcement, outcomes included reductions in unnecessary truck rolls and improvements in parts-identification and first-visit fix rates, reflecting targeted quality and field service objectives.
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United States Army | Government | 453551 | $65.3B | United States | IBM | IBM Predictive Maintenance and Quality (PMQ) | Quality Management | 2017 | n/a |
In 2017, LOGSA contracted with IBM to deploy IBM Predictive Maintenance and Quality for the United States Army as part of a Watson IoT initiative. The deployment targeted vehicle maintenance analytics within the United States, using IBM Predictive Maintenance and Quality to support Quality Management of Army fleets.
The implementation integrated Watson IoT capabilities to ingest onboard sensor streams and historical maintenance records, feeding IBM Predictive Maintenance and Quality to run predictive analytics and prescriptive maintenance modeling. Functional capabilities implemented included failure prediction models, condition-based monitoring, and generation of prescriptive maintenance insights, all aligned with Quality Management processes and vehicle readiness workflows. A proof of concept was executed on the Stryker fleet to validate predictive detection of maintenance failures using onboard telemetry and maintenance logs.
Operational scope focused on logistics and maintenance functions within the Army, with LOGSA coordinating the contract and initial program rollout, and an intent to extend predictive and prescriptive maintenance insights across Army vehicle fleets in the United States. Governance and rollout planning centered on phased expansion from the Stryker proof of concept to broader fleet deployments, aligning sustainment commands, maintenance operations, and quality assurance workflows to consume IBM Predictive Maintenance and Quality outputs.
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Buyer Intent: Companies Evaluating IBM Predictive Maintenance and Quality (PMQ)
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FAQ - APPS RUN THE WORLD IBM Predictive Maintenance and Quality (PMQ) Coverage
IBM Predictive Maintenance and Quality (PMQ) is a Quality Management solution from IBM.
Companies worldwide use IBM Predictive Maintenance and Quality (PMQ), from small firms to large enterprises across 21+ industries.
Organizations such as NVIDIA, United States Army, Faurecia and Sears Home Improvement Prods are recorded users of
IBM Predictive Maintenance and Quality (PMQ) for Quality Management.
Companies using IBM Predictive Maintenance and Quality (PMQ) are most concentrated in Manufacturing, Government and Automotive, with adoption spanning over 21 industries.
Companies using IBM Predictive Maintenance and Quality (PMQ) are most concentrated in United States and France, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of IBM Predictive Maintenance and Quality (PMQ) across Americas, EMEA, and APAC.
Companies using IBM Predictive Maintenance and Quality (PMQ) range from small businesses with 0-100 employees - 25%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 0%, and global enterprises with 10,000+ employees - 75%.
Customers of IBM Predictive Maintenance and Quality (PMQ) include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified IBM Predictive Maintenance and Quality (PMQ) customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Quality Management.