The key players operating in the Overall Equipment Effectiveness Software Market are overall equipment effectiveness software market size is expected to grow from USD 67.5 billion in 2023 to USD 122.4 billion by 2028, at a CAGR of 12.6%. The increase in the use of ERP software for performing various functions within industries, the need for a connected supply chain and mass production to cater to the rising population, and the rising adoption of IoT and AI across manufacturing industries globally are the major driving factors for the growth of the overall equipment effectiveness software market. Moreover, the rise in the integration of manufacturing execution systems with enterprise resource planning and product lifecycle management, as well as rapid developments in wireless sensor networks, are some factors that are also expected to drive the growth of the market in the near future. , DRIVER: Rising usage of ERP software for performing a variety of functions across industries , Organizations have adopted cloud ERP models to identify which model best aligns with their strategy, workloads, and security requirements, thus adopting the best cloud ERP solution. Some of the benefits of cloud ERP systems for organizations are such as avoiding the need to pay for all computer platforms, including hardware platforms and data server platforms, cutting IT services and support since the data center offers IT support, and replacing paying ahead for application software licensing. , RESTRAINT: High initial capital investments and growing maintenance and upgradation costs , The investment cost of OEE software includes consultation, acquisition, adjustment, implementation, and running costs, which subsequently increase a company’s expenditures. , Consultation cost: It includes the cost of consultations and discussions before implementing manufacturing execution systems. This stage also comprises the investigation and decision-making processes, specifying the updated requirements of an enterprise based on trial runs. Moreover, before using a manufacturing execution system, every company needs to investigate the benefits of the system individually. Therefore, organizations need to identify their requirements, which helps in making the right decision. This can be best ensured by consultation. , Acquisition cost: This includes all the costs that arise at the beginning of a project and are associated with the actual purchase of the system. It comprises hardware, system software, application software, and installation costs. , OPPORTUNITY: Rising integration of MES with PLM and ERP solutions , Manufacturing execution systems perform various functions, such as managing products and resources, scheduling, dispatching, collecting data, analyzing performance, and auditing data. For the smooth functioning of these processes and effective results, manufacturing execution systems are integrated with various solutions, such as ERP, supply chain management (SCM), warehouse management system (WMS), decision support system (DSS), business intelligence, e-commerce. For example, the integration of manufacturing execution systems with WMS enables the maintenance of orders that come into the warehouse. To feed the data in the system accurately and promptly, an order management system within the MES solution is used. , CHALLENGE: Growing concerns regarding integration issues of certain OEE software with legacy systems , System complexities and implementation costs are still the major challenges organizations face while integrating these solutions with their existing systems. Due to the lack of resources, only some organizations still rely on existing systems that use old technologies, where manual processes lead to a high error rate and long turnaround time. Moreover, because legacy systems underuse are mostly on-premises, integrating these systems with new cloud-based systems might challenge adopting digital process automation solutions and services. , Overall Equipment Effectiveness Software Ecosystem , Prominent companies in this market include well-established, financially stable developers and providers of overall equipment effectiveness software. These companies have been operating in the market for several years and possess a diversified product portfolio, state-of-the-art technologies, and strong sales and marketing networks. Prominent companies in this market include Siemens (Germany), Schneider Electric (France), ABB (Switzerland), Emerson Electric, Co. (US), and Rockwell Automation (US). , Software segment to hold the largest share of the market in 2022 , The software segment holds the largest market share in 2022 due to factors such as increasing adoption of automation, advanced analytics capabilities, integration with other software systems, scalability and flexibility, and the growing focus on productivity and efficiency improvement. These software solutions play a crucial role in monitoring and optimizing equipment performance in automated processes, providing real-time data, performance metrics, and analytics dashboards. The ability to analyze and optimize equipment performance, along with their compatibility with other enterprise systems, makes OEE software highly sought after by industries looking to improve operational efficiency and remain competitive in the market. , On-premises segment to dominate the overall equipment effectiveness software market in 2022 , In 2022, the on-premises segment held the largest equipment effectiveness software market share. On-premises deployment eliminates the reliance on external networks or internet connectivity. Manufacturers can access and utilize the OEE software locally within their facilities without concerns about network stability or latency issues. This ensures uninterrupted access to critical information and real-time monitoring, enabling prompt decision-making and response to equipment performance issues. The widespread adoption of on-premises deployment in OEE software is because it provides organizations with control, customization, security, compliance, and compatibility with existing infrastructure, addressing their specific needs and preferences. , Predictive maintenance is estimated to hold the highest CAGR during the forecast period , The core function of predictive maintenance is to precisely predict asset failure, thereby enabling enterprises to take the asset out of production just before it fails and ensure production is not hampered due to the asset’s failure. Predictive maintenance is estimated to hold the highest CAGR during the forecast period as organizations increasingly recognize the value of proactive equipment maintenance to enhance overall equipment effectiveness. Predictive maintenance OEE software utilizes advanced analytics, machine learning, and sensor data to predict and prevent equipment failures, reducing unplanned downtime and optimizing production efficiency. , Healthcare to be the largest growing industry during the forecast period , The healthcare industry is expected to hold significant growth in the overall equipment effectiveness software market during the forecast period owing to the increasing focus on operational efficiency and cost optimization to meet the growing demand for healthcare services while maintaining high-quality patient care. OEE software helps track and analyze the utilization of medical equipment such as diagnostic machines, surgical tools, imaging devices, and patient monitoring systems. By collecting real-time data on equipment usage and downtime, healthcare providers can identify inefficiencies, optimize scheduling, and ensure that equipment is available when needed, thereby maximizing its utilization. , Asia Pacific region is likely to hold the largest growth rate by 2028 , The Asia Pacific region is experiencing rapid industrial automation adoption. Companies are implementing advanced technologies such as robotics, IoT (Internet of Things), and AI (Artificial Intelligence) to streamline their manufacturing operations. These technologies enable businesses to automate production, improve efficiency, and optimize equipment utilization. OEE software plays a crucial role in this automation journey by providing real-time monitoring, performance analysis, and predictive maintenance capabilities to maximize equipment efficiency. The major factor driving the growth of the overall equipment effectiveness software market in APAC is the increasing focus of manufacturers toward industrial automation and smart manufacturing. , Recent Developments , In June 2022, Siemens acquired Senseye, a leading provider of AI-powered solutions for industrial machine performance and reliability. This acquisition will enable Siemens to expand its predictive maintenance and asset intelligence portfolio. , In May 2022, Schneider announced version 22.0 of EcoStruxure Automation Expert to provide end-to-end digital continuity through close integration with AVEVA applications. EcoStruxure can connect to AVEVA Engineering to import plant design data for automated bulk systems. , In April 2022, ABB signed a partnership agreement with Samsung Electronics to innovate holistic energy management solutions to drive the growth of smart building technology. The development is aimed at enabling ABB to expand customer access to home automation technologies and device management solutions. , KEY MARKET SEGMENTS , By Overall Equipment Effectiveness Software Methods: , Availability Calculation , Performance Calculation , Quality Calculation , Real-Time Monitoring , Root Cause Analysis , Predictive Analytics , By Offering: , Software , Services , By Deployment Mode: , On-premises , Cloud , By Type: , Supervisory Control And Data Acquisition (SCADA) , Manufacturing Execution System (MES) , Cloud Enterprise Resource Planning (ERP) , Predictive Maintenance , Data Historian , By Industry , Aerospace & Defense , Automotive , Chemical , Food & Beverage , Healthcare , Metal & Mining , Oil & Gas , Power , Electronics & Semiconductor , Others , By Region: , North America , Europe , Asia Pacific (APAC) , Rest of the World (RoW), KEY MARKET PLAYERS , Siemens , Schneider Electric , ABB , Emerson Electric, Co. , Rockwell Automation.
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