Alternatives to aspenONE Asset Performance Management (APM)

The SBS QMS Suite consists of 5 software modules that work together for efficient Quality compliance: 1) SBS Quality Database - CAPA / 8D corrective and preventive actions (CAR) with root cause analysis - Nonconformance management - Risk analysis including FMEA, SWOT, interested party risk register - Internal, customer, and third-party audit management - Environmental Health and Safety (EHS / HSE) management 2) SBS Ground Control - Employee training management (LMS) - Self-Paced training - Change control - Document control 3) SBS Asset Tracking Database - Calibrated equipment control - Preventive maintenance - Asset inventory management 4) SBS Inspection Database - Record incoming material, in process, and final product inspection data - Generate real time SPC charts - Inspection plans and Control Plans - Archive data for further statistical analysis 5) SBS Vendor Management - Maintain an approved vendor list or AVL - Develop vendor / supplier qualification plans - Maintain vendor / supplier qualification history Modules may be purchased separately or in any combination. On-premise and cloud-based options are available. Free demos are available for download or contact us for a cloud-based demo.

The Asset Guardian (TAG) Mobi: Tackle Downtime with TAG Mobi TAG Mobi is a fully embedded preventive maintenance and asset management (EAM) solution within Microsoft Dynamics 365 Business Central. Designed for modern manufacturing and infrastructure operations, TAG Mobi helps reduce risk, minimize downtime, and streamline maintenance workflows—all from within your existing Business Central environment. From proactive asset health monitoring and predictive maintenance to real-time mobility and AI-powered adoption tools, TAG Mobi equips maintenance teams with everything they need to boost performance and take control of asset operations. Key Features: • Fully embedded in Microsoft Dynamics 365 Business Central • Real-time mobile access for on-the-go asset tracking • Predictive maintenance to reduce unplanned downtime • AI-assisted onboarding for faster adoption • Advanced APM tools to monitor asset health and anticipate failures No silos. No extra software. Just a seamless, native experience that empowers maintenance teams and provides managers with the insights they need—right inside Business Central.

It works: Codeless testing Give your entire team the ability to create and maintain automated tests. Not just developers. Meet your testing demands fast. You can get full coverage of your tests in days and not months. Our natural-language tests are very resistant to code changes. Our AI will quickly repair any test failures. Continuous Testing is a key component of Agile/DevOps. Push features to production in the same day. Boozang supports the following test approaches: - Codeless Record/Replay interface - BDD / Cucumber - API testing - Model-based testing - HTML Canvas testing The following features makes your testing a breeze - In-browser console debugging - Screenshots to show where test fails - Integrate to any CI server - Test with unlimited parallel workers to speed up tests - Root-cause analysis reports - Trend reports to track failures and performance over time - Test management integration (Xray / Jira)

eMaint, a cloud-based Computerized Maintenance Management System (CMMS), is an award-winning software that helps organizations improve their ability to manage their maintenance reliability operations, equipment, and compliance. eMaint is suitable for any size company or enterprise. It integrates all the tools they require into one powerful platform, saving companies valuable time and money. It includes maintenance scheduling, work order management, reports and dashboards as well as predictive maintenance, preventive maintenance and mobile maintenance. It also manages inventory management and asset management.

DigitalClone®, for Engineering is the only software that integrates multiple scales of analysis into a single package. It is the world's best gearbox reliability prediction tool. DC-E, in addition to the modeling and analysis capabilities at the level of the gearbox and the gear/bearing, is the only software that models fatigue life using detailed, physics-based models (US Patent 10474772B2). DC-E allows the construction of a digital twin of a gearbox. This includes all stages of the asset's lifecycle, from design and manufacturing optimization to supplier selection to failure root cause analysis to condition based maintenance and prognostics. This computational environment reduces the time and cost of bringing new designs to market and maintaining them over time.

Epsagon allows teams to instantly visualize, understand, and optimize their microservice architectures. With our unique lightweight auto-instrumentation, gaps in data and manual work associated with other APM solutions are eliminated, providing significant reductions in issue detection, root cause analysis and resolution times. Epsagon can increase development speed and reduce application downtime.

Achieve production targets and financial objectives while minimizing unexpected disruptions. Utilizing status dashboards and automated alerts, operations personnel and managers are informed of potential failures, granting them the opportunity to pinpoint and resolve issues before they escalate into expensive challenges. Transition to predictive and prescriptive maintenance approaches that tackle known failure points and declines in performance without incurring additional costs. By recognizing leading indicators of potential breakdowns, you can eliminate the need for expensive preventive part replacements that may not be necessary. Employ advanced analytics, data mining, and data visualization techniques to swiftly and accurately uncover root causes, revealing hidden patterns within the data. This enables you to troubleshoot performance problems more effectively and gain insight into their origins, allowing for rapid corrective measures to be implemented. Ultimately, this proactive approach not only enhances operational efficiency but also fosters a culture of continuous improvement within the organization.

Identify patterns in operational data that can forecast deterioration and potential failures long before they occur. By employing accurate failure pattern recognition, you can reduce the frequent occurrence of false positives typically associated with traditional model-based approaches. Utilizing low-touch machine learning, you can swiftly distinguish between normal and abnormal behaviors, ensuring equipment protection starts within weeks rather than extending into months. The integration of Aspen Mtell with Aspen Cloud Connect™ provides connectivity to devices that support OPC UA. This method of recognizing operational patterns not only serves as an initial defense against asset decline but also enhances existing maintenance strategies through the deployment of AI-driven agents across various sites or throughout the entire organization. By focusing on precise failure pattern recognition, the challenge of high false positive rates in model-based solutions is effectively mitigated. Moreover, the rapid identification of operational behaviors facilitates timely equipment protection, ensuring that organizations can respond proactively to potential issues as they arise.

Harnessing digital transformation enhances the value of your resources and allows for the integration of predictive maintenance (PdM) techniques. By anticipating potential issues, you can avert expensive breakdowns, minimize downtime, and direct your efforts towards future innovations. Our extensive Asset Performance Management (APM) software suite is specifically crafted to address contemporary industrial obstacles by utilizing industrial big data, cloud computing, artificial intelligence, digital twin technology, and augmented reality. With enhanced analytical capabilities, you can eradicate inefficiencies, streamline operations, and boost your bottom line. This cohesive multi-dimensional information framework aggregates data from various origins, providing meaningful context for reporting and dashboard applications. Elevate your plant's performance in near real-time by facilitating detailed analytics in your business intelligence tools centered around industrial data. By connecting your workforce, processes, and technology, you can swiftly implement a risk-based asset management strategy aligned with your organizational goals, ensuring a resilient and adaptable operational framework for the future.

A comprehensive solution for monitoring and predictive analysis can enhance equipment condition tracking and streamline maintenance and repair processes. This involves utilizing predictive analysis to ensure production process quality and assess potential risks of exceeding maximum permissible loads through detailed unit operation evaluations. By implementing predictive analysis of unit conditions, emergency shutdowns can be effectively minimized. Furthermore, evaluating the quality of repair work by comparing equipment performance before and after servicing is critical for continuous improvement. The integration of automatic controls for manual repair and maintenance tasks enables efficiency and accuracy in operations. Additionally, predictive analysis aids in strategic maintenance and repair decisions while facilitating informed purchases of new equipment based on intelligent load balancing of current assets. Spare parts and consumables can also be optimized through intelligent failure predictions, reinforcing a proactive approach to equipment management. Overall, this solution supports a robust framework for enhancing operational reliability and efficiency.

Accruent Observe offers a comprehensive IoT solution for remote monitoring, management, and energy optimization across various types of equipment, aimed at enhancing energy efficiency and operational performance while also predicting equipment failures, improving air quality, and ensuring compliance with commercial refrigeration standards. By maintaining facilities and assets at their optimal performance levels, organizations can effectively meet both compliance requirements and financial objectives. Unplanned downtime can be significantly reduced by pinpointing the exact moment an asset starts to fail, allowing for proactive maintenance to address issues before they escalate. This approach enables businesses to replace equipment solely when necessary instead of adhering to arbitrary schedules, leading to a reduction in unnecessary service costs and overall maintenance expenditures. Moreover, users can identify which locations and equipment are the largest energy consumers, enabling real-time monitoring of energy usage, with the capability to filter by energy type or date range, thus facilitating timely corrections of excessive energy consumption. Additionally, from the initial purchase to disposal, organizations can gain complete visibility into the entire lifecycle of refrigerant usage, ultimately resulting in substantial cost savings. Finally, by leveraging data analytics, businesses can make informed decisions that further enhance operational efficiency and sustainability.

Actively oversee the health of machines and plants to maintain maximum uptime, productivity, and address maintenance requirements effectively. Utilize the advantages of analytics along with Industrial IoT technologies to achieve a more comprehensive understanding of equipment on the plant floor, facilitating predictive maintenance capabilities. Keeping an eye on machine health is essential to minimize production interruptions that stem from unexpected failures and outages. By promoting predictive maintenance, the time required to assess machine health issues can be significantly reduced, while also enhancing the traceability of historical data. Integrate IT and OT data into a unified viewpoint to bridge the gap between plant floor information and MES data, thereby enabling more informed decision-making processes. Employ real-time data gathering and integrated analytics to monitor live data concerning machine health and performance, assess machines against optimal conditions, and issue early warnings about potential disruptions, which in turn helps in lowering overtime labor costs, scrap rates, emergency maintenance expenses, and adverse impacts on profit and loss. This comprehensive approach not only enhances operational efficiency but also fosters a culture of proactive management across the manufacturing process.

Shield34 stands out as the sole web automation framework that ensures complete compatibility with Selenium, allowing users to seamlessly continue utilizing their existing Selenium scripts while also enabling the creation of new ones through the Selenium API. It effectively tackles the notorious issue of flaky tests by implementing self-healing technology, intelligent defenses, error recovery protocols, and dynamic element locators. Furthermore, it offers AI-driven anomaly detection and root cause analysis, which facilitates a swift examination of failed tests to identify what changed and triggered the failure. By eliminating flaky tests, which often present significant challenges, Shield34 incorporates sophisticated defense-and-recovery AI algorithms into each Selenium command, including dynamic element locators, thereby reducing false positives and promoting self-healing alongside maintenance-free testing. Additionally, with its real-time root cause analysis capabilities powered by AI, Shield34 can swiftly identify the underlying reasons for test failures, minimizing the burden of debugging and the effort required to replicate issues. Ultimately, users can relish a more intelligent version of Selenium, as it effortlessly integrates with your existing testing framework while enhancing overall efficiency.

Producers like yourself possess the expertise required to maneuver through the intricate hurdles of remaining competitive in today’s market landscape. This is applicable across a wide range of sectors, including pharmaceuticals, consumer goods, food and beverage, mining, and chemicals. Therefore, embracing the latest technological innovations is essential for advancing your ongoing digital transformation efforts. Throughout your organization, from the control room to executive meetings, users of process systems consistently grapple with the challenge of optimizing productivity while managing budget limitations and resource availability, all while tackling shifting operational risks. By addressing these challenges head-on, you can unlock significant productivity enhancements across your facility with the PlantPAx distributed control system (DCS). The features of this system can greatly influence the lifespan of your plant operations, ensuring that integrated and scalable systems enhance productivity, boost profitability, and minimize operational risks. Ultimately, investing in such advanced systems can lead to a more resilient and efficient production environment.

Power Factors’ Drive platform serves as a sophisticated cloud-based solution for managing the performance of renewable energy assets. This innovative software provides a comprehensive suite of tools designed for owners, operators, and asset managers, enabling them to effectively monitor, manage, and enhance the performance of their renewable assets, encompassing everything from operational oversight to detailed reporting and technical management. Building upon the data framework of the Drive platform, Drive Pro offers enhanced analytic capabilities that foster collaboration among stakeholders at every stage of asset performance management, which includes elements such as plant design, predictive modeling, and operations and maintenance (O&M). To complement these functionalities, our asset-focused enterprise asset management (EAM) system, Drive O&M, integrates flawlessly with the Drive platform, ensuring that operational events, maintenance records, and compliance obligations for each asset are interconnected. Furthermore, the incorporation of automated workflows and classifications for failures significantly contributes to maximizing the asset's lifespan while also optimizing O&M processes. This holistic approach not only enhances the efficiency of asset management but also supports sustainable energy initiatives.

OPUS is a leading platform for industrial no-code AI that allows users to model equipment and processes. With OPUS you can benefit from: - Process optimization insights - Predictive maintenance - Lower power consumption - Increased productivity - Accurate forecasting - Increased asset reliability - Reduced maintenance costs - Improved planning - ESG reporting and carbon reduction insights Without programming or coding experience, existing teams can get insights from their data and predict future outcomes. Explore your asset's data deeper than ever before. Uncovering unexpected correlations. Root cause analysis can be done on individual components to help you focus your efforts. Automated AI predictive insights can help you plan interventions and make informed business decisions. With rapid deployment and AI model results within minutes of being built, you can unleash the power of your existing operational data and achieve real ROI, using your existing team of asset engineers, operators and maintenance managers. Optimize your entire facility, plant, or work site, discover the power of automated AI.

The Robust Intelligence Platform is designed to integrate effortlessly into your machine learning lifecycle, thereby mitigating the risk of model failures. It identifies vulnerabilities within your model, blocks erroneous data from infiltrating your AI system, and uncovers statistical issues such as data drift. Central to our testing methodology is a singular test that assesses the resilience of your model against specific types of production failures. Stress Testing performs hundreds of these evaluations to gauge the readiness of the model for production deployment. The insights gained from these tests enable the automatic configuration of a tailored AI Firewall, which safeguards the model from particular failure risks that it may face. Additionally, Continuous Testing operates during production to execute these tests, offering automated root cause analysis that is driven by the underlying factors of any test failure. By utilizing all three components of the Robust Intelligence Platform in tandem, you can maintain the integrity of your machine learning processes, ensuring optimal performance and reliability. This holistic approach not only enhances model robustness but also fosters a proactive stance in managing potential issues before they escalate.

Ensure the upkeep and efficiency of physical assets by leveraging real-time data, the Internet of Things (IoT), machine learning, mobile solutions, and advanced predictive analytics. Enhance the planning, scheduling, and execution of maintenance tasks through the integration of smart technologies that offer fresh value and streamline your operations. Disseminate exemplary methods for the effective deployment, oversight, and maintenance of machinery. Improve the management of assets and customer service workflows with a centralized database for all asset and equipment details. Minimize equipment downtime and boost asset productivity through an automated system for monitoring equipment utilization. This comprehensive approach not only enhances operational efficiency but also fosters a culture of continuous improvement in asset management practices.

As industries advance technologically, maintaining plant profitability through a structured and accountable maintenance program has become essential. MP2 is a fully integrated asset management solution that allows companies to efficiently organize inventory, oversee equipment expenses, monitor equipment history, schedule preventive maintenance, keep confidential labor records, allocate resources, generate work orders, and requisition or purchase necessary parts, all while projecting potential equipment failures. Suitable for facilities of any size, MP2 can be installed on either standalone or client/server systems. Additionally, it boasts a seamless upgrade feature; users can input data into the standalone version and later transition to a client/server setup without needing to re-enter data, ensuring a smooth evolution of their maintenance practices. This remarkable flexibility and user-friendliness have made MP2 the preferred choice among maintenance professionals globally, often surpassing other management systems in popularity. Ultimately, the robustness of MP2 positions companies to thrive in increasingly competitive environments.

Deductive AI is an innovative platform that transforms the way organizations address intricate system failures. By seamlessly integrating your entire codebase with telemetry data, which includes metrics, events, logs, and traces, it enables teams to identify the root causes of problems with remarkable speed and accuracy. This platform simplifies the debugging process, significantly minimizing downtime and enhancing overall system dependability. With its ability to integrate with your codebase and existing observability tools, Deductive AI constructs a comprehensive knowledge graph that is driven by a code-aware reasoning engine, effectively diagnosing root issues similar to a seasoned engineer. It rapidly generates a knowledge graph containing millions of nodes, revealing intricate connections between the codebase and telemetry data. Furthermore, it orchestrates numerous specialized AI agents to meticulously search for, uncover, and analyze the subtle indicators of root causes dispersed across all linked sources, ensuring a thorough investigative process. This level of automation not only accelerates troubleshooting but also empowers teams to maintain higher system performance and reliability.

InsightFinder Unified Intelligence Engine platform (UIE) provides human-centered AI solutions to identify root causes of incidents and prevent them from happening. InsightFinder uses patented self-tuning, unsupervised machine learning to continuously learn from logs, traces and triage threads of DevOps Engineers and SREs to identify root causes and predict future incidents. Companies of all sizes have adopted the platform and found that they can predict business-impacting incidents hours ahead of time with clearly identified root causes. You can get a complete overview of your IT Ops environment, including trends and patterns as well as team activities. You can also view calculations that show overall downtime savings, cost-of-labor savings, and the number of incidents solved.

Enhancing reliability, performance, and safety stands as a primary focus for industrial enterprises and businesses in the current landscape. Organizations are channeling their resources and efforts into managing expenses effectively while striving to maximize value from their existing assets. AVEVA Predictive Analytics empowers these organizations to achieve optimal returns on essential assets by facilitating predictive maintenance (PdM) initiatives. The AVEVA Predictive Analytics solution offers advanced early warning notifications and diagnostics for equipment problems, potentially identifying issues days, weeks, or even months before they lead to failures. This proactive approach allows asset-heavy organizations to minimize equipment downtime, boost reliability, and enhance performance, all while decreasing operational and maintenance costs. Furthermore, AVEVA Predictive Analytics seamlessly integrates with various control and monitoring systems and supports deployment either on-premises or in a cloud environment. Its highly scalable architecture enables the monitoring of anything from a single asset to entire plants or even hundreds of remote assets spread across multiple locations, ensuring comprehensive oversight and management capabilities. Ultimately, this solution aids organizations in navigating the complexities of asset management in an increasingly competitive market.

Sensai offers a cutting-edge AI-driven platform for detecting anomalies, performing root cause analysis, and forecasting issues, which allows for immediate problem resolution. The Sensai AI solution greatly enhances system uptime and accelerates the identification of root causes. By equipping IT leaders with the tools to effectively manage service level agreements (SLAs), it boosts both performance and profitability. Additionally, it automates and simplifies the processes of anomaly detection, prediction, root cause analysis, and resolution. With its comprehensive perspective and integrated analytics, Sensai seamlessly connects with third-party tools. Users benefit from pre-trained algorithms and models available from the outset, ensuring a swift and efficient implementation. This holistic approach helps organizations maintain operational efficiency while proactively addressing potential disruptions.

Senseye PdM employs advanced proprietary machine learning techniques to anticipate potential asset failures before they occur. By automatically evaluating the performance of your machinery, Senseye can accurately forecast when maintenance should be performed. This allows maintenance teams to prioritize their efforts on the assets that require the most urgent care. With an easy-to-implement solution, organizations can reduce maintenance expenses while enhancing the accuracy of downtime predictions. Designed for scalability, Senseye PdM can accommodate any number of connected machines, whether large or small. The automated condition monitoring provides insights that emphasize only the most pertinent information. Users gain an understanding of how long their machinery is expected to operate before maintenance is necessary. The platform allows for the seamless analysis of tens of thousands of assets, providing a clear and ongoing indication of which machines need attention. Furthermore, Senseye ensures that industrial companies experience significant reductions in machine downtime, ultimately leading to enhanced operational efficiency and productivity.

Effortlessly design, execute, and evaluate tests with a focus on enhancing collaboration among development, testing, product, and DevOps teams, enabling them to deliver high-quality products in record time. Leverage your tests in a production environment while tracking business transactions efficiently. CloudBeat is designed for DevOps and developers alike, offering cross-region, device, and browser compatibility. It also enables comprehensive monitoring of user experience and service level agreements (SLAs), providing an in-depth performance analysis. With features such as intelligent root-cause analysis, real-time alerts, and daily updates, it supports both SaaS and on-premise deployment. This centralized continuous quality platform streamlines the creation, execution, and assessment of unit, API, integration, and end-to-end tests within a DevOps setting. Furthermore, CloudBeat integrates effortlessly with leading testing frameworks and CI tools, allowing for the execution of extensive test suites through built-in parallelization, test lab oversight, and failure analysis. Our goal is to elevate your software quality, minimize testing and development durations, and ultimately enhance customer satisfaction. By utilizing CloudBeat, teams can ensure a more efficient workflow and achieve better results.

Safeguard business service-level agreements by utilizing dashboards that enable monitoring of service health, troubleshooting alerts, and conducting root cause analyses. Enhance mean time to resolution (MTTR) through real-time event correlation, automated incident prioritization, and seamless integrations with IT service management (ITSM) and orchestration tools. Leverage advanced analytics, including anomaly detection, adaptive thresholding, and predictive health scoring, to keep an eye on key performance indicators (KPIs) and proactively avert potential issues up to 30 minutes ahead of time. Track performance in alignment with business operations through ready-made dashboards that not only display service health but also visually link services to their underlying infrastructure. Employ side-by-side comparisons of various services while correlating metrics over time to uncover root causes effectively. Utilize machine learning algorithms alongside historical service health scores to forecast future incidents accurately. Implement adaptive thresholding and anomaly detection techniques that automatically refine rules based on previously observed behaviors, ensuring that your alerts remain relevant and timely. This continuous monitoring and adjustment of thresholds can significantly enhance operational efficiency.

Sightline EDM: Improved Operations, Right Out of the Box Predictive analytics and performance and risk-based monitoring used to be a complicated process. Between endless Excel files and disjointed communication between departments, a lot of information was lost. When you switch to Sightline EDM, you can start making the best decisions for your operations, prepare for the future, and begin saving time and money immediately in one easy-to-use platform. One Easy-to-Use Dashboard Data from multiple monitoring tools can be consolidated into a single display: a uniform, easy-to-use dashboard with drill-down details. Real-Time OT & IT Intelligence With configurable notifications to any errors or anomalies, visualize and analyze production and operations in minutes, not months. Scalable Usability for All Organizations & Teams Proven, enterprise-grade, scalable software solution with role-based access controls, security, and user views that works with all web browsers and mobile devices. Pre-Built Integrations Across Systems Data from PLCs, CNC machines, process equipment, ERP/MES systems, and other vital data sources is gathered in minutes, not months, using open, agent, and agentless interfaces.

Arize's machine-learning observability platform automatically detects and diagnoses problems and improves models. Machine learning systems are essential for businesses and customers, but often fail to perform in real life. Arize is an end to-end platform for observing and solving issues in your AI models. Seamlessly enable observation for any model, on any platform, in any environment. SDKs that are lightweight for sending production, validation, or training data. You can link real-time ground truth with predictions, or delay. You can gain confidence in your models' performance once they are deployed. Identify and prevent any performance or prediction drift issues, as well as quality issues, before they become serious. Even the most complex models can be reduced in time to resolution (MTTR). Flexible, easy-to use tools for root cause analysis are available.

Enhancing asset performance is essential for boosting reliability and availability while also cutting costs and minimizing operational risks. Asset Performance Management (APM) encompasses a comprehensive range of software and services aimed at improving the efficiency of operations and maintenance across various equipment, the overall plant, and the entire fleet. With advanced features like Digital Twin analytics, work process automation, and integrated GE industry knowledge, APM delivers distinct advantages for contemporary industrial operations. By facilitating proactive monitoring and safeguarding of critical assets and systems, APM helps mitigate unplanned downtime, thereby enhancing both availability and reliability. Additionally, it plays a vital role in ensuring the health and safety of employees, environmental protection, and the achievement of business objectives by minimizing asset-related incidents. Furthermore, by enabling early detection of issues, APM transforms potential unplanned downtimes into planned and scheduled maintenance activities, significantly reducing the need for costly emergency repairs. Ultimately, this strategic approach not only preserves asset integrity but also fosters a more efficient and sustainable operational framework.

Connect2Assets empowers maintenance teams to utilize real-time condition information seamlessly integrated into their current workflows. Upon receiving a notification, users can efficiently generate a work order, input failure codes, reserve spare parts, and log labor hours directly within the Connect2Assets application. Moreover, tasks can be managed effectively by attaching supplementary documentation to the work order, which may include drawings, operational instructions, or wiring schematics. Additionally, users can link their existing automation systems to their EAM/CMMS solution, enabling the software to intelligently supervise the equipment under its management. By utilizing existing PLC/SCADA-generated condition and process data points, teams can monitor asset health without the need for new hardware purchases. Connect2Assets consolidates industrial data from various sites and integrates it with IBM Maximo, allowing users to access previously untapped SCADA/PLC data. This integration enhances decision-making in maintenance by providing a wealth of data, ultimately leading to more effective maintenance strategies and improved operational efficiency. Consequently, the ability to harness this extensive data stream empowers teams to proactively address maintenance issues before they escalate.

Fluke Connect™ software enables the collection, storage, and visualization of machine data from over 80 Fluke tools and sensors. This data is now securely stored in the cloud, allowing teams to access it effortlessly via their smart devices or computers. Whether it’s data from condition monitoring sensors or portable test instruments, maintenance and reliability teams are empowered with comprehensive information to make crucial decisions and perform essential tasks. By implementing remote sensors that automatically upload data to the cloud, time-consuming manual rounds can be significantly reduced. This innovation eliminates the need for clipboards, discrepancies, and data silos, ensuring that asset information is readily available on smart devices. Additionally, Fluke Connect Condition Monitoring™ software provides teams with the ability to analyze asset trends through graphical representations sourced from connected monitoring devices. By facilitating thorough data analysis, personnel can gain valuable insights that help in predicting asset conditions and minimizing the risk of unexpected downtime. Ultimately, this enhances overall operational efficiency and reliability.

Harness the power of AI for anomaly detection and root cause analysis focused on the key metrics that impact your business. Avora employs machine learning to oversee your business metrics around the clock, promptly notifying you of critical incidents so you can respond within hours instead of waiting for days or weeks. By continuously examining millions of records every hour for any signs of unusual activity, it reveals both potential threats and new opportunities within your organization. The root cause analysis feature helps you identify the elements influencing your business metrics, empowering you to implement swift, informed changes. You can integrate Avora’s machine learning features and notifications into your applications through our comprehensive APIs. Receive alerts about anomalies, shifts in trends, and threshold breaches via email, Slack, Microsoft Teams, or any other platform through Webhooks. Additionally, you can easily share pertinent insights with your colleagues and invite them to monitor ongoing metrics, ensuring they receive real-time notifications and updates. This collaborative approach enhances decision-making across the board, fostering a proactive business environment.

Eugenie's robust decision-making framework empowers industrial companies to extract maximum value from their assets and processes. At Eugenie, we seamlessly integrate AI as a powerful yet invisible force that enhances operational efficiency and dependability in industrial settings. Our platform is designed to foster a harmonious blend of technology, efficiency, and trust. With a distinctive framework centered on Explainable AI, Eugenie provides decision-makers with actionable, data-driven insights. Equipped with thorough root-cause analysis and predictive capabilities, the digital ecosystem of Eugenie facilitates informed decision-making processes. The collaborative environment within Eugenie harmonizes human abilities with machine intelligence. By adopting an AI-first strategy, Eugenie prioritizes user-centric design to enhance the reliability of both machines and processes. We view technology as a vital partner in boosting human productivity. Additionally, Eugenie's agile digital infrastructure is tailored to rapidly generate insights for industrial applications, ensuring that organizations can adapt swiftly to changing conditions. This commitment to innovation positions Eugenie as a leader in transforming industrial operations for the better.

BQR's integrated solution, apmOptimizer, is used to optimize asset maintenance and logistics. It also serves as a strategic tool for asset design or overhaul. Using a flexible model that accounts for failures, inspections and maintenance, as well as downtime, cost, spare parts, maintenance, up time, and cost, apmOptimizer calculates expected asset behavior. Optimizer's modules help to determine the best maintenance and logistics policy, which minimizes the Life Cycle Cost (LCC), while still maintaining high asset availability.

Functions independently to manage regular alerts and actions, thereby minimizing escalations and mitigating burnout. It intelligently modifies thresholds and dashboards to proactively avert incidents and updates runbooks with each new occurrence. This efficiency can save on-call engineers as much as 20 hours weekly, allowing them to focus on development tasks. It manages all alerts, conducts root cause analysis, resolves incidents, and ensures that the on-call experience is stress-free. By automating root cause analysis and incident response, it can reduce Mean Time to Resolution (MTTR) by up to 80%. With comprehensive incident summaries and hypotheses accessible prior to logging in, users will enjoy quicker response times and significantly enhanced uptime. Getting started is quick and easy with production-ready AI that is secure and adept in utilizing all necessary production tools just like a seasoned software engineer. Additionally, it automatically maps your production environment, comprehends code, and tracks modifications seamlessly without requiring any prior training. This innovative approach not only streamlines operations but also enhances overall productivity and efficiency within the team.

The SAP Digital Manufacturing Cloud provides a comprehensive manufacturing execution system (MES) that enables the execution of processes, scenario analysis, and system integration using an efficient Industry 4.0 framework. It allows key stakeholders to gain insights into manufacturing performance at both global and plant levels through user-friendly, preconfigured analytics. By consolidating various manufacturing operations management (MOM) and automation systems, it connects multiple solutions and standard-based interfaces for streamlined data acquisition. Furthermore, it promotes ongoing business enhancement by employing advanced algorithms and machine learning to speed up root-cause analysis. As a result, businesses can meet highly individualized market demands, manage significant product variability, and enhance customer satisfaction while also preserving productivity, profitability, and quality standards. This holistic approach ultimately positions organizations to navigate the complexities of modern manufacturing more effectively.

Parallel Asset is a sophisticated Computerised Maintenance Management System (CMMS) tailored to oversee every aspect of the maintenance cycle throughout the lifespan of your assets. Our uniquely crafted platform integrates streamlined workflow tiers with enhanced asset management frameworks, which not only extend the longevity of your equipment and facilities but also reduce costs and minimize downtime. Whether in sectors like energy, nuclear, military, or commercial infrastructure, Parallel Asset offers seamless adaptability to meet diverse industry needs. By leveraging intelligent systems paired with real-world experience and data, Parallel Asset efficiently handles all Maintenance Work Requests, Work Orders, and Workpacks in alignment with your specific maintenance philosophy and framework. Fully equipped to optimize your assets according to their vulnerability strategies and operational goals, our CMMS platform stands out as a comprehensive solution for maintenance management. This innovative approach ensures that your organization can maintain peak operational efficiency while effectively managing its resources.

The management of asset integrity is crucial in conservative sectors such as energy, oil, and gas, where the effective handling of intricate equipment is essential. Facilities in these industries demand exceptional performance across a wide array of metrics, including revenue, compliance, quality, safety, energy efficiency, and operating costs. VAIL-Plant stands out as a premier, fully certified Asset Integrity Software Solution, specifically developed for the oil and gas, power, and petrochemical sectors, to streamline inspection and maintenance management processes through methodologies like RBI, RCM, SIL, and FMECA. This comprehensive asset management tool plays a significant role in safeguarding the health and efficiency of a company’s assets by empowering plant operators to enhance their oversight of asset conditions through optimized inspection routines and seamless integration with maintenance systems. By utilizing VAIL-Plant, organizations can ensure not only compliance with industry standards but also drive continuous improvement in their operations.

You can gain a deeper understanding of your organization by using workforce analytics, deep-dive visualisation, org charts and reporting tools. Use machine learning to automate root cause analysis and problem detection in HR. Predict the impact and outcome of organizational changes in order to remain proactive and responsive. Modernize your organizational design by embracing continuous AI-driven design. This will help you build the future state for your organization. The business team builds a well designed organization that can scale and adapt quickly to change while retaining talent more effectively and hiring more efficiently. The finance teams can see the forecasted budgets for HR through predictive reporting.

Our AI and IoT (AIoT) solutions empower clients to make informed business decisions by leveraging real-time data on the usage of their onsite equipment, which in turn enhances their capacity to improve customer service, logistics, and sales opportunities. By monitoring onsite temperature and performance in real-time, businesses can anticipate potential failures in refrigerators, vaccines, tests, and medications, thereby improving reliability. This technology allows for continuous performance tracking of machinery, enabling the delivery of value-added services while gaining insights into product usage. By adopting a proactive approach, companies can enhance customer satisfaction and provide valuable insights that promote optimal operational efficiency. Furthermore, it helps optimize compliance for in-store appliances and machinery while minimizing both inventory and maintenance expenses. In the food and beverage industry, chain stores manage thousands of locations, each equipped with multiple appliances, yet often lack the capability to effectively monitor and track the usage of these devices, which can lead to inefficiencies. Ultimately, implementing AIoT technology can transform the way businesses operate, fostering a culture of continuous improvement and greater accountability in appliance management.

IBM® Z® Operations Analytics is a powerful tool designed to facilitate the searching, visualization, and analysis of extensive structured and unstructured operational data within IBM Z environments, encompassing log files, event records, service requests, and performance metrics. By utilizing your analytics platform alongside machine learning, you can enhance enterprise visibility, pinpoint workload issues, uncover hidden challenges, and expedite root cause analysis. Machine learning aids in establishing a baseline of typical system behavior, enabling the detection of operational anomalies efficiently. Additionally, you can identify nascent issues across various services, allowing for proactive alerts and cognitive adjustments to evolving conditions. This tool offers expert recommendations for corrective measures, enhancing overall service assurance. Furthermore, it helps in spotting atypical workload patterns and reveals common problems that may be obscured in operational datasets. Ultimately, it significantly diminishes the time needed for root cause analysis, thereby capitalizing on the extensive domain knowledge of IBM Z and applying its insights effectively within your analytics framework. By harnessing these capabilities, organizations can achieve a more resilient and responsive operational environment.

The IBM Maximo® Application Suite comprises a collection of applications designed for effectively monitoring and managing assets, as well as for predictive maintenance and reliability planning. Maximo Application Suite enables organizations to maximize the value derived from their enterprise assets through a unified, cloud-based platform that harnesses the power of AI, IoT, and analytics to enhance performance, prolong asset lifespans, and minimize both operational downtime and expenses. Equipped with IBM Maximo's leading-edge technology, users benefit from adaptable applications for CMMS, EAM, APM, and RCM, all while enjoying simplified installation and management processes, alongside an improved user experience through the integration of shared data and workflows. Utilizing AI and analytics allows for effective management and maintenance of high-value assets, which not only optimizes their performance but also extends their operational lifecycles and decreases costs and downtime. By incorporating automated asset inspections that are powered by real-time data and artificial intelligence, organizations can significantly enhance their inspection procedures. This comprehensive suite ensures that users are well-prepared to meet the challenges of asset management in today’s fast-paced business environment.

Traversal is an innovative AI-driven Site Reliability Engineering (SRE) solution that functions round the clock, autonomously identifying, addressing, and even preventing production issues. It meticulously analyzes logs, metrics, traces, and your codebase to pinpoint the root causes of errors or delays, quickly highlighting the impacted areas, critical bottleneck services, and potential root causes with relevant evidence in a matter of minutes. Leveraging advancements in causal machine learning, reasoning from large language models, and intelligent AI agents, Traversal proactively resolves problems before alerts are triggered, ensuring seamless operations. Tailored for complex organizations and vital infrastructure, it accommodates diverse data types, supports bring-your-own models, and offers optional on-premises deployment for added flexibility. With its straightforward integration into existing systems requiring only read-only access—without the need for agents, sidecars, or any write operations to production—Traversal guarantees data privacy and control. By effortlessly fitting into your observability framework, it not only accelerates the resolution process but also significantly reduces downtime, further enhancing operational efficiency and reliability. Furthermore, its ability to adapt to various environments makes it a versatile asset for businesses striving for uninterrupted service delivery.

Small Hours serves as an AI-driven observability platform designed to diagnose server exceptions, evaluate their impact, and direct them to the appropriate personnel or team. You can utilize Markdown or your current runbook to assist our tool in troubleshooting various issues effectively. We offer seamless integration with any stack through OpenTelemetry support. You can connect to your existing alerts to pinpoint critical problems swiftly. By linking your codebases and runbooks, you can provide necessary context and instructions for smoother operations. Rest assured, your code and data remain secure and are never stored. The platform intelligently categorizes issues and can even generate pull requests as needed. It is specifically optimized for enterprise-scale performance and speed. With our 24/7 automated root cause analysis, you can significantly reduce downtime while maximizing operational efficiency, ensuring your systems run smoothly at all times.

Apollo Root Cause Analysis™ is a method grounded in principles that aids individuals in mastering effective strategies for problem-solving. When paired with the RC Pro® software, it enables the development of a comprehensive, evidence-based comprehension of any issue encountered. Such an understanding of the root causes and their effects fosters solutions that gain acceptance across the entire organization. The Apollo Root Cause Analysis™ approach promotes the establishment of a shared understanding through collaboration with all relevant stakeholders, resulting in a solid evidence-based perspective on the problem at hand. This methodology guarantees that the solutions implemented tackle verified causes, thereby minimizing the chances of future occurrences. It simplifies the problem-solving process and equips trained individuals with the necessary skills to tackle real-world challenges more efficiently and effectively. Additionally, RC Pro serves as a versatile root cause analysis software solution that can be customized for businesses of any scale and in various sectors. By utilizing RC Pro, organizations can enhance and integrate their problem-solving capabilities, leading to improved outcomes. Ultimately, this synergy between Apollo Root Cause Analysis™ and RC Pro empowers teams to create lasting solutions that foster continuous improvement.