An ADMS is the decision support environment that provides a shared network model (a digital twin of an electric distribution network) and a common user experience for all roles that are needed to monitor, control and orchestrate assets across the grid while optimizing and securing operations of the grid. The ADMS assists electricity distribution system operators to proactively and safely guide outage restoration activities, manage and optimize networks for improved asset utilization, and effectively manage the integration and impact of distributed energy resources (DERs). ADMS functions include: Distribution state estimation (DSE) Fault location, isolation and restoration (FLISR) Volt/volt-ampere reactive optimization (VVO) Outage management Conservation through voltage reduction (CVR) Peak-demand management Integration of distributed energy resources
The application development life cycle management (ADLM) tool market focuses on the planning and governance activities of the software development life cycle (SDLC). ADLM products focus on the 'development' portion of an application's life. Key elements of an ADLM solution include: software requirements definition and management, software change and configuration management, software project planning, with a current focus on agile planning, work item management, quality management, including defect management. Other key capabilities include: reporting, workflow, integration to version management, support for wikis and collaboration, strong facilities for integration to other ADLM tools.
Computer-Aided Design software is used by designers, engineers, architects, and drafters across several industries to create two-dimensional and three-dimensional models. These 2D and 3D models can be used to explore design ideas, visualize concepts and simulate the physical behavior of a design in the real world. The software provides in-built templates such as flowcharts, mind maps, wireframes, network diagrams, and org charts to create quality as well as detailed design models. The software also allows for instant changes to models enabling collaborative work between team members.
Data center infrastructure management (DCIM) tools monitor, measure, manage and/or control data center resources and energy consumption of both IT-related equipment (such as servers, storage and network switches) and facilities infrastructure components (such as power distribution units and computer room air conditioners). They are data-center-specific (they are designed for data center use), rather than general building management system tools, and are used to optimize data center power, cooling and physical space. Solutions do not have to be sensor-based, but they do have to be designed to accommodate real-time power and temperature/environmental monitoring. They must also support resource management, which Gartner defines as going beyond typical IT asset management to include the location and interrelationships between assets.
Gartner defines enterprise agile planning (EAP) tools as products that enable organizations to scale their agile practices to support a holistic enterprise view. These tools act as a hub for defining, planning, managing and deploying work. They also serve as an information hub for the disparate islands of metrics from the full life cycle. Just as agile is an evolution of development methodologies, EAP tools are an evolution of project-/team-centric tools. They support a business-outcome-driven approach to managing the full life cycle of agile product delivery at scale. EAP tools in this market combine data from multiple sources to enable: - Monthly, weekly and even daily incremental value delivery based on business outcomes - Support for enterprise agile frameworks like Scaled Agile Framework (SAFe) - Product roadmapping - Management of strategy, investments and objectives - Increased visibility into the flow of work - Management of work backlogs - Collaboration capabilities for individuals and teams - Management of cross-team dependencies - Release planning and forecasting - Visibility into the financial aspects of the work being done
The global industrial IoT platform delivers multiple integrations to industrial OT assets and other asset-intensive enterprises’ industrial data sources to aggregate, curate and deliver contextualized insights that enable intelligent applications and dashboards through an edge-to-cloud architecture. The global industrial Internet of Things (IIoT) platform market exists because of the core capabilities of integrated middleware software that support a multivendor marketplace of intelligent applications to facilitate and automate asset management decision making. IIoT platforms also provide operational visibility and control for plants, infrastructure and equipment. Common use cases are augmentation of industrial automation, remote operations, sustainability and energy management, global scalability, IT/operational technology (OT) convergence, and product servitization of industrial products. The IIoT platform monitors IoT endpoints and event streams, supports and/or translates a variety of manufacturer and industry proprietary protocols, analyzes data in the platform, at the edge and in the cloud, integrates and engages IT and OT systems in data sharing and consumption, enables application development and deployment and can enrich and supplement OT functions for improved asset management life cycle strategies and processes. In some emerging use cases, the IIoT platform may obviate some OT functions.
Integration means making independently designed applications and data work well together. IoT integration means making the mix of new IoT devices, IoT data, IoT platforms and IoT applications — combined with IT assets (business applications, legacy data, mobile, and SaaS) — work well together in the context of implementing end-to-end IoT business solutions. The IoT integration market is defined as the set of IoT integration capabilities that IoT project implementers need to successfully integrate end-to-end IoT business solutions.
Manufacturing process management (MPM) and model-based manufacturing (MbM) bridge the gap between the virtual design realm and the physical product/process manufacturing realm as part of an organized software architecture. These technologies are not only applied within the four walls of a plant or a corporation's multiple manufacturing sites. They can be applied holistically, with workflow to manage multiple recipe variants and labeling change/requirements, and/or handle certificates of compliance (CoCs) and certificates of analysis (CoAs) from suppliers.
Gartner defines manufacturing execution systems (MES) as a specialist class of production-oriented software that manages, monitors and synchronizes the execution of real-time physical processes involved in transforming raw materials into intermediate and/or finished goods. These systems coordinate this execution of work orders with production scheduling and enterprise-level systems like ERP and product life cycle management (PLM). MES applications also provide feedback on process performance, and support component and material-level traceability, genealogy and integration with process history, where required.
MDMS products are IT components of the advanced metering infrastructure (AMI). The core MDMS is responsible for cleansing, calculating and providing the data persistence of commodity consumption data. Additional MDMS capabilities now include disseminating metered consumption data for internal as well as external use. Meter data can be used to support billing, as well as analytics use cases, such as load profiling, consumption tracking, forecasting, asset loading and revenue protection, including the detection of tampering, theft or leakage. Beyond supporting internal utility needs, MDMS plays a role in open consumption data by supporting the sharing of consumption data with customers, partners, market operators and regulators. In most markets, data sharing is done with standardized data exchange formats.
Gartner defines multienterprise collaboration networks (MCNs) as solutions that support a community of trading partners of any tier and type that need to coordinate and execute on business processes extending across multiple enterprises. Gartner considers cloud-based MCNs to be a key technology to coordinate, orchestrate and automate an organization’s extended supply chain within the overall business ecosystem they operate in. The key capabilities of MCN solutions include three layers: Network representation and management, Application functions, Embedded analytics and intelligence.
Product life cycle management (PLM) is a philosophy, process and discipline supported by software for managing the life cycle of products through the stages from concept through recycling/retirement. As a discipline, it has grown from a mechanical design and engineering focus to being applied to many different vertical-industry product development challenges. The market for PLM software includes vendors that: - Provide product data management (PDM) software to capture, cultivate and manage technical product-related content. That content defines the products’ specifications and designs and their allowable product configurations. It includes technical descriptions of the parts, materials and allowable product configurations expressed as 3D models, drawings and other related content. All PLM vendors deliver PDM functionality. - If software providers support only PDM functionality, Gartner does not consider them PLM vendors. PLM vendors support complementary applications that enable the PLM discipline to various degrees. Gartner considers a vendor a PLM provider if it supports at least three complementary software categories that enable the PLM discipline. Table 1 provides insight into the complementary categories of software that support the PLM discipline. Those additional software categories help manufacturers create, deliver, maintain, service and discontinue products.
Gartner defines the market for quality management system (QMS) software as the business information management system that manages quality policies and standard operating procedures (SOPs). This may include, but is not limited to, customer requirements, quality documents, International Organization for Standardization (ISO) requirements, manufacturing capabilities, robust design, auditing procedures and protocols, nonconformance/risk management activities, testing criteria, and industry-specific regulations (for example, U.S. Food and Drug Administration [FDA] or Federal Acquisition Regulation [FAR] requirements).
Supervisory control and data acquisition (SCADA) software is essential for industries such as manufacturing, energy and utilities, transportation etc. to control the processes, collect & monitor real-time data, and communicate system issues. The software communicates with devices such as programmable logic controllers (PLCs) and Remote Terminal Units (RTUs) to interact with industrial equipment and processes. SCADA software can be run virtually, which allows the operator to supervise the industrial processes even from a distant location. The software provides real-time data insights through Human Machine Interface (HMI) to maximize efficiency, reduce overhead costs, and streamline operations. The software also warns the operator of any hazardous conditions such as blocked processes and failing systems.
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