- What Is Asset Performance Management?
Gartner defines Asset Performance Management (APM) as a market of software tools and applications designed to improve the reliability and availability of physical assets (such as plants, systems of equipment, and infrastructure) essential to the operation of an enterprise. It is an umbrella term for all the technologies focused on improving the performance of a physical asset. - What Is Condition Based Maintenance?
Condition based maintenance (CBM) is equipment maintenance executed when certain indications imply performance degradation. CBM uses the data of an asset to determine its usage and actual status. On a basis of the asset data performance decrease, upcoming asset failure can be determined and certain trends can be identified. - What Is Predictive Maintenance?
Predictive maintenance (PdM) is the scheduling of maintenance based on indications from different systems. PdM takes the maintenance one step further compared to condition based maintenance by looking at the patterns across all sensors and predicting asset failure rather than reacting when certain indications imply performance degradation. - What Is Prescriptive Maintenance?
Prescriptive Maintenance (RxM) is a type of maintenance that leverages all of the mentioned technologies (machine learning, Internet of Things (IoT) and big data analytics) in order to produce outcome-focused recommendations for operations and maintenance. It not only predicts asset failure but is also able to offer actionable solutions while measuring the impact of the recommended solutions on the affected operations. - What Is a Digital Twin?
Digital twin is a virtual replica of a physical asset or a system. It incorporates all the technology used in Prescriptive Maintenance and is the last step in optimising asset performance management. Essentially, it is technology that takes real-world data about a physical asset as input and produces predictions or realistic simulations on that asset as output. Digital twins can be manipulated in order to optimise the performance of that physical asset. - How Do I Get Started?
Usually, we follow a simple process consisting of 4 steps:
Data Scan – we conduct a 2-3-day asset data scan on your critical assets to evaluate the organisation’s data quality, availability and completeness;
Business Case – we then work together and assess if there is an opportunity for a business case within the organisation;
(optional) Organisation Readiness – we assess whether the company has a clear strategic commitment towards entering Industry 4.0 and the right resources and processes to take immediate action;
Proof of Concept – we then work together in order to create a proof of concept for a tailored solution within the company.
If you have more questions regarding the process, feel free to contact us. - Do I Own the Data?
Generally, the owner of the asset is also the owner of the data. In case you want to create additional services based on the asset data, more detailed agreements will be made for the data ownership. - Is My Data Safe?
In most cases, we provide our software on premise running on a server of the customer or a private cloud. Our customers take care of the data security and we support the requirements. In case of a cloud offering, we are also using different security protocols including advanced encryption and hiding, amongst others. - How Long Does the Implementation Take?
The length of implementation is dependent on the urgency of the transformation and the available resources. Apart from that, the quality, availability and completeness of the current asset data is also important. Fast implementation can be finished within weeks but larger and more complex projects could take more time. - Where Can I Deploy the Software?
Our APM software can be deployed on a large variety of hierarchical levels:On a chip in a device;
On edge computers managing different devices;
On a server, both on-premise or in the cloud. - How Do I Use the APM Studio Software?
Our platform is user-friendly, easy-to-use and is designed for engineers and others to use with a low/no coding approach. Just by dragging and dropping, you are able to set up the logic and processing to create your Asset Performance Management application. The ease of use does not decrease the high customisability of the software though. You will, of course, receive the initial training, user manual of the software and the support of our experts. - Is it possible to define and perform comprehensive reliability, maintenance, and mechanical integrity analytical functions, including asset strategy identification and execution, within a single platform?
APM Studio integrates condition-based monitoring (CBM), predictive maintenance (PdM), and Bowtie cause-consequence models (bringing your FMEA/FMECA’s live on streaming data) for defining and managing asset strategies. The platform uses Digital Twins for real-time asset monitoring and analysis, while automated workflows and Decision Support Rules ensure the effective execution of maintenance actions automatically to your EAM or CMMS. Object models, classes, and multi-level deployment options help visualize, scale, and manage large quantities of data and assets efficiently. Additionally, Complex Event Processing (CEP) allows real-time event correlation and proactive response, making APM Studio a robust tool for digitization of asset services on a single platform. - What types of integrations are available with SAP models, including but not limited to SAP MDM, SAP PM, and SAP HR? Can you explain in detail how your technology supports these integrations?
Asset and process notifications, at different severity and priority levels, generated by APM Studio, can be queried by a wide range of EAMs and CMMSes that support REST-API interfaces. All events necessary to be broadcasted in APM Studio can be configured to be available for EAM/CMMS integration. Certain EAM/CMMS vendors that support IoT interfaces can subscribe to the continuous MQTT event streams of an APM-Studio solution. - How does the system generate work orders, notifications, and triggers based on events or conditions?
APM Studio has the capability to generate work orders, notifications, and triggers based on specific events or conditions by leveraging its capability of Processing Rules (enabling CBM, PdM and ML Algorithms), Complex Event Processing (CEP), and Decision Support Rules. The platform uses CEP to continuously analyze streams of events and alarms, identifying critical conditions in real-time. When a condition is met, the CEP engine can trigger actions such as generating notifications or initiating workflows. Additionally, Decision Support Rules interact with users to determine the appropriate responses, which can include generating work orders or other corrective actions. APM Studio also integrates seamlessly with Enterprise Asset Management systems (EAM) Computerized Maintenance Management Systems (CMMS) by providing REST Services, allowing your systems to query and automatically create work orders from the detected events and conditions, ensuring a smooth maintenance workflow and timely response to asset needs. - How can data be exposed for querying through Business Intelligence (BI) tools?
APM Studio has REST API capability meaning that all the insights provided by processing rules, alarms, notifications, decision support rules et cetera can be made available for querying for other external applications and parties as required. Since APM Studio comes with an integrated time-series database, these insights and their history are easily available. Also, it is important to mention that APM Studio can run “headless” meaning running only as a server without UI providing the processed insights to the BI tools. - How does the solution provide visibility into asset health and generate alarms and alerts?
APM Studio provides comprehensive visibility into asset health by continuously monitoring data and evaluating key performance indicators (KPIs) that can be fully customized. The platform can generate alarms and alerts based on predefined conditions or unexpected changes in asset behavior, ensuring that maintenance teams are promptly notified of potential issues. - How does the system facilitate Failure Modes, Effects, and Criticality Analysis (FMECA) and Reliability Centered Maintenance (RCM) based on industry standards?
APM Studio facilitates Failure Modes, Effects, and Criticality Analysis (FMECA) and Reliability Centered Maintenance (RCM) by using BowTie cause-consequence models to bring these analyses to life on streaming data. The BowTie method enables real-time monitoring of potential failure causes and their consequences by linking risk models to live asset data. This approach helps in identifying failure mechanisms early, continuously assessing risk, and supporting proactive maintenance decisions. By integrating these models with live data streams, APM Studio ensures that FMECA and RCM processes are dynamic and aligned with industry standards, improving reliability and reducing asset risks. - How does the system identify and report assets causing significant issues (bad actors)?
By continuously monitoring asset performance and analyzing key metrics, the platform can detect recurring problems or underperforming assets. Through dashboards and alerts, APM Studio highlights these bad actors, allowing maintenance teams to prioritize actions and focus on resolving the underlying issues. Users can filter alarm browsers and dashboards to showcase the worst-performing assets first, and also low-performance KPIs will instantly bring attention to bad actors. - How does the platform support both quantitative and qualitative risk assessment approaches?
APM Studio supports both quantitative and qualitative risk assessment approaches. Quantitative assessments include processing rules that enable condition monitoring and predictive maintenance, as well as running Machine Learning models, KPIs, and generating alarms/notifications based on live streaming data from assets. Cause-consequence models are used in both quantitative and qualitative assessments; for example, FMEA/FMECAs, which are qualitative by nature, can be brought live on streaming data, making them quantitative. Decision Support Rules support qualitative assessments by guiding users through prescriptive steps to resolve issues. - How can hazard analysis and what-if scenarios be performed for asset risk management?
APM Studio supports hazard analysis and what-if scenarios for asset risk management by leveraging its powerful cause-consequence models. These models allow users to simulate various risk conditions and evaluate their potential impacts in a controlled environment (connected to data from the field). In What-If mode, the central Alarm is created when at least one cause of the Bowtie is confirmed by its Controls. This mode is typically used for monitoring conditions in your application (i.e. you want to prevent something from happening and act or notify your users early). APM Studio’s Testing capability further enhances this by enabling users to tweak parameters and observe how the system responds, effectively running customized what-if scenarios. - How does the platform ensure smooth interaction between APM and other systems such as EDMS, Field Rounds, mMDM, SAP HR, SAP PM, Historian, and EPMS?
APM Studio achieves this by offering a range of integration options, including REST APIs (and their documentation), native connectors, and standardized data exchange protocols. Native connectors include OPC UA for industrial automation, Open Industry 4.0 (OI4) Open Edge Communication, MQTT for IoT devices, Modbus, REST API, Azure Blob Storage, Endress+Hauser’s Netilion, and SQL databases. These capabilities allow APM Studio to communicate effectively with external systems, enabling seamless data sharing and process coordination. This integration ensures that insights generated within APM Studio are easily accessible to other enterprise systems, supporting comprehensive asset and operations management across the organization. - What role-based visualizations are available, and how do they display information specific to an end-user’s role and responsibilities?
APM Studio provides role-based visualizations to ensure that the information displayed is tailored to the end-user’s role and responsibilities. Dashboards and interfaces are configured to present relevant data based on user roles, such as maintenance personnel, operators, or managers. This targeted approach helps users focus on the most relevant information, improving efficiency and decision-making by displaying only what is necessary for their specific responsibilities. Role-based access also ensures that users interact with the platform in a way that aligns with their operational needs and authority. - How does the system support analysis of an asset’s remaining useful life (RUL)?
APM Studio supports the analysis of an asset’s remaining useful life (RUL) by using predictive maintenance techniques and integrating machine learning models, specifically survival analysis models through its Python Server. The platform uses historical and real-time data to assess the current condition of assets and predict their future performance. - How can custom dashboards be created to display various metrics and KPIs?
Dashboards in APM Studio are interactive and connect to data sources, KPIs, alarms, and objects, displaying data in various formats such as tables, line charts, bar charts, dials, and embedded views like alarm browsers. Users can create different components (without coding), such as meters for KPI monitoring or buttons for setting asset properties, ensuring that the right data is available in a user-friendly format. Dashboards serve as a central location to display information from multiple sources, enhancing visibility, streamlining monitoring, and supporting proactive maintenance actions by presenting key data in an intuitive and accessible way. - How does the system generate condition-based equipment reports that summarize the status and condition of assets, including asset health indicators, with drill-down capabilities?
APM Studio supports the automatic creation of customized PDF or Markdown documents, tailored to the user’s preferences including the context and data of assets. These reports can be shared periodically via communication platforms such as Microsoft Teams, Email, or Slack, ensuring that relevant stakeholders receive timely updates on asset conditions and performance. - What services are available for validating business processes, setting up integrations, and configuring user roles and security settings?
APM Studio assists users in ensuring that business processes align with operational goals by providing validation tools and support. This includes using real-time analytics of asset and process performance, linking them to business processes through KPIs and detailed reporting. By continuously monitoring performance data, APM Studio helps validate whether operational activities are meeting predefined business objectives, enabling users to make informed adjustments. Integration capabilities and interfaces are available to connect APM Studio seamlessly with other systems, such as ERP, EAM or CMMS, ensuring smooth data exchange and operational efficiency. Additionally, APM Studio provides flexible options for configuring user roles and security settings, allowing organizations to define access levels and maintain secure control over asset data and operations. - What comprehensive training materials and adoption management services are provided to ensure effective use of the APMS technology?
UReason provides comprehensive training materials and adoption management services to ensure effective use of the APM Studio. The platform includes extensive documentation that covers all aspects of APM Studio’s functionality, complete with practical reference projects that allow users to learn through hands-on experience. In addition, APM Studio features an in-app help section that guides users directly to explanations for specific components and their usage. To support successful adoption, UReason offers onboarding workshops where customers are trained to use the platform efficiently hands-on, ensuring they can fully make use of its capabilities in their operations. - How does the system support Reliability, Availability, and Maintainability (RAM) models?
By making use of data from performance monitoring, historical performance, and predictive maintenance analytics, APM Studio enables users to build RAM models that assess the reliability of assets, predict availability, and optimize maintenance strategies. These models help identify potential bottlenecks, estimate asset downtime, and improve overall system reliability, allowing organizations to make informed decisions to maximize operational efficiency. - What features are available to support Root Cause Analysis (RCA)?
APM Studio supports Root Cause Analysis (RCA) by using cause-consequence models and decision support rules. The cause-consequence models help visualize the chain of events that lead to a failure, allowing users to understand and trace back potential root causes. Additionally, decision support rules guide users step-by-step through structured RCA processes, prompting relevant questions and recommending actions to mitigate issues. - How does the platform support Asset Criticality Analysis (ACA)?
APM Studio supports Asset Criticality Analysis (ACA) by providing tools to assess and rank assets based on their impact on overall operations. By leveraging data such as failure history, maintenance records, operational dependency, and KPIs, APM Studio helps users determine the criticality of each asset in terms of safety, production, and maintenance priorities. The platform uses alarms, processing rules, and decision support rules to evaluate asset performance, identify failure trends, and assess potential risks. This data-driven approach helps users prioritize assets effectively. - What options are available for manual data import/export within the platform?
Users can import data from various formats, such as CSV, to update or add asset information, historical records, or other relevant data. Similarly, data can be exported manually for reporting and analysis. - How does the system support manual data entry for users?
APM Studio supports manual data entry, allowing users to input information directly into the system. Through decision support rule forms, customized in-process data entry forms for inspection round can easily be set-up. - Please provide a holistic overview of your standard asset health program and the value it can bring to customer.
APM Studio provides customer the capability to move to a risk-informed decision-making process that will support customer in maintaining a high asset health level and at the same time keeping acceptable asset/process risk ALARP (As Low as Reasonably Practicable).The risk-based decision-making process is provided by APM Studio on the basis of knowing what is happening (24/7monitoring using engineering knowledge combined with ML models), how this is happening (using cause models) and how it will affect the processes (using consequence models). As APM Studio uses Bowtie models (graphical cause-consequence models) it can easily explain to the users, in a graphical fashion, why certain failure-mechanisms are active, how these related to causes and what barriers will lead to further future consequences. - Please describe your understanding of condition based, predictive and prescriptive maintenance, including an overview or your standard, out-of-the box offering.
Condition Based Maintenance: Maintenance at times determined/driven by the usage of the equipment performed after one or more problems have been signalled.
Real-time condition monitoring enhances CBM, in APM Studio, by calculation of the likelihood of unwanted events (24/7) on the basis of available data from the asset.
Predictive Maintenance: Extends real-time condition monitoring in combination with historical data used to continuously evaluate asset/system health and signal a failure-mode/breakdown before it happens.
Prescriptive Maintenance: Extends Predictive Maintenance and provides the user insight into reasons for expected breakdowns, consequences (effects) and guides the users in the decision making process dealing with the expected breakdowns (recommendations).Out of the box APM Studio provides real-time condition monitoring, predictive and prescriptive models for a variety of asset types (typicals) and allows the user to extend these and create new ones. APM Studio can run near the assets (on Chip or Edge compute), on premise and in Cloud. Insights gained 24/7 by APM Studio can be connected easily to CMMS systems to create jobs-orders. - Please describe your standard typical approach (from pilot to roll-out) for condition based, predictive and prescriptive maintenance solutions.
UReason’s standard approach for real-time CBM, PdM and Prescriptive solutions consists of 4 steps: 1) Asset Selection, 2) Data Collection, 3) Modelling and 4) Deployment.1) Asset Selection: Assets are selected based on their high contribution to downtime/cost/risk and low failure frequency.
2) Data Collection: For assets selected, and related assets in the process, data is collected from data historians, EAMS systems (CMMS and AMS) and OEE systems (if available)
3) Modelling: Based on a selection of the highest RPNs in the FMECAs of the assets selected engineering models are configured/set-up and machine learning models for early classification of failure-mechanisms are trained and validated. In addition, advisory streams (for interaction) are set-up using Decision Support rules in APM-Studio.
4) Deployment: Engineering and ML models are deployed, monitored for accuracy and maintained
If sufficient data is available to deploy ML models with a high enough accuracy and lead-time (time from classification/detection to failure) ML models are deployed part of the cause-consequence models (Bowties). - Please describe how you would apply your standard asset health offerings on different criticality levels of assets and why?
We advise to apply PdM for High/Medium critical assets and CBM for Medium/Low critical assets. PdM capabilities for less critical assets – Medium/Low – could also be established but typically requires additional time in the Modelling phase. However, if the vision of the customer is to go towards a hand-off/lights-out approach we do advise also to consider PdM for Medium/Low assets.
Prescriptive we advise irrespective of the asset criticality classification in case knowledge near the assets is not abundant or degrading. - For AI/ML predictive models, do you use mathematical / physical, hybrid or pure data driven models? Please explain in detail.
APM Studio supports the execution of PMML models and allows these to be combined with deterministic and probabilistic models. Results of 1st principle and simulation models can be integrated into the object model representing the process or part of the process using interfaces such as SOAP and/or REST-API. As APM Studio also provide a Python Server your Data Science results can easily be productized and linked to data/sementic models in APM Studio. - Please describe how your out-of-the box solutions can drive local maintenance and service organizations to higher maturity levels.
In our experience, the successful introduction of digital maintenance solutions requires the local maintenance and service organization to take ownership of the new solution. Our software APM Studio has been especially designed to empower domain experts to become creators of such solutions and not mere users of black-box models. As creators, the teams will naturally take ownership of the new solutions. The UX of APM Studio allows new users to quickly get comfortable with the models and function corresponding to their current maturity level. Within days users are therefore familiar with the software. The low – code / no – code design of APM Studio allows them then to step by step develop to the next maturity levels. Example: Maintenance organizations which have built their condition monitoring application in APM will automatically start to explore machine learning solutions as it is the obvious next step in APM Studio. - If your solution(s) leverage equipment/maintenance data points typically not available in the DCS (e.g, vibration, ultrasound, temperature, etc.) – please describe how your solution(s) will allow such data points to flow to Data Lake.
For installations where vibration, ultrasound and other sensory data is not available in the DCS/Process Historian we need to assess the data sources in question to provide a suitable solution in order to unlock this data. We have a broad experience tapping into such data sources using interfaces such as OPC DA, OPC UA, MQTT and SQL Server to unlock data from Bently Nevada systems and alike.For other applications we can provide NOA compliant hardware + store and forward to on-premises, cloud solutions allowing you to unlock data from 4-20mA HART, Fieldbus/Profibus/Profinet/Ethernet IP systems leveraging our partner-eco system products for protocol conversion. Partner eco-system vendors: Pepperl&Fuchs, Phoenix Contact, Wago, Hilscher. In both cases APM Studio can be used for heavy data loading and analysis (near to the assets on Edge compute virtual or physical) and forward aggregated results and analysis results via OPC UA/MQTT to the servers, cloud for further usage. - What type of services can be provided by UReason (e.g. project implementation, smaller pieces of work such as change requests, training, value discovery workshops, …)?
UReason provides the following types of services to its customers: product training, data analysis, model training and validation, solution engineering and/or co-development for CBM and PdM applications. - Are demo environments available over the Internet? Or do you have a standalone demo of your solution(s)?
Both are available. UReason can provide APM Studio on managed Cloud Infrastructure or a standalone demonstration system running on customer hardware. - What type of support can you provide after implementation?
Application, monitoring, maintenance, support, life-cycle management and consulting. - What is your deployment and release strategy / methodology (patches, upgrade, hotfixes, …)?
APM Studio uses the typical versioning ‘code-of-conduct’: <<Version>>.<<Revision>>.<<Patch>>. Major releases contain major functionality updates. Revisions extend existing/enhance existing functionality. Patch versions provide fixes for reported issues. Forward compatibility is important to us – configurations done/made in APM Studio older versions/revisions can always be run in later versions/revisions.
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