White Papers



  Title Summary  
  A Data Infrastructure to Transform Operations Across all industries, there are assets everywhere, all generating critical time series data. As the volume and sources of asset data constantly expand, there are multiple challenges to creating insights that impact operational performance. Operators, engineers and managers face a data deluge that comes from diverse systems and has a heterogeneous array of units, protocols and formats. For analysis and reporting, users often wrestle with data stored in multiple systems with very little associated context. The difficulty surrounding accessing, finding and integrating vital operational data in a timely manner often results in underutilization for initiatives such as asset health, product quality and genealogy or process efficiency. What’s needed is an environment that breaks down these barriers. An environment that connects all operational information sources in a coherent and scalable way and empowers people to leverage data to generate the insight that leads to actionable information, best practices, analysis and continuous improvement. An infrastructure.
  A Journey from Historian to Infrastructure As technology lowers barriers to large scale data capture, industries are searching for ways to capitalize on information; however, very few have standardized technologies that allow data to create impact at an enterprise scale. More often, operational ecosystems encompass single purpose technologies, such as traditional historians, that limit exposing information to multiple people or purposes. While invaluable for local visibility, implementing numerous single purpose technologies across the enterprise leads to multiple versions of the truth, information islands and layers of legacy systems. In this environment, people often struggle to access, analyze or share data especially outside organizational, geographical or security boundaries. Data remains underutilized or “dark” for key business drivers such as asset health, process efficiency and quality.
  A New Era in Mill Analytics Today, every mill faces the challenge of optimizing production management decisions. These decisions, such as rationalizing grade structures, enable the supply chain to respond to the realities of shorter product life cycles. In this environment, treating data as an enterprise asset enables the stakeholders to operate and manage independently based on near real-time, data-driven insights. Given the potential return, every mill can justify retooling their decision-support systems so they can track profitability by asset, by customer and by run throughout the life cycle of each grade. Accelerating time-to-market through data-driven decision-making may be one of the more compelling justifications for treating data as an enterprise asset. Recent advances in how process data are collected, stored and visualized across the enterprise are revolutionizing the way mills relate operational performance to cost structure.
  Architecting an Industrial Sensor Data Platform for Big Data Analytics For decades, organizations have been evolving best practices for IT (Information Technology) and OT (Operation Technology). With the evolution of the IIoT (Industrial Internet of Things) promoting machines with more sensors and corresponding data, there is a greater propensity to apply Big Data and analytics strategies to OT (Operations Technology) centric processes and discrete sensor-based operations technology and data. The amalgamation of Big Data and OT strategies, approaches and data is now revealing novel operational and business insights. Insights that are delivering transformational process, asset health, energy, safety, regulatory and quality improvements.
  Challenges, Opportunities and Strategies for Integrating IIoT Sensors with Industrial Data Ecosystems Today’s Industrial Internet of Things (IIoT) encompasses advances in sensor technologies, connectivity, analytics and cloud environments that will expand the impact of data on enterprise performance management. Recent market analysis predicts that lowered sensor cost, energy requirements and ease of connectivity will result in an explosion of industrial sensors and sensor-based data. For example, Cisco’s Internet Business Solutions Group predicts that by 2020, 50 billion IIoT devices will be deployed and active.
  Challenges, Opportunities and Strategies for Integrating OT and IT with the Modern PI System Over the last several decades, as industries transitioned from analog and pneumatic controls to digitalized PLCs, DCS and SCADA systems, Operational Technologies (OT) have provided plant personnel with ever increasing volumes of data to monitor, optimize and control industrial processes; however, there has not been a clear path for organization to leverage this data outside of OT domains. Differences in IT and OT functions, technology stacks and cultures have created significant barriers to OT-IT convergence.
  Condition-Based Maintenance Bolsters the Bottom Line in Power Generation The power generation industry is undergoing a period of rapid transformation. New issues, such as deregulation, the rapid adoption of renewable energy sources, and a new emphasis on extending facility lifecycles, are forcing electric utility operators to carefully consider how they expend their resources and optimize their operations.
  Connecting IIoT Assets to the PI System Expands Enterprise Visibility and Intelligence Over the last several decades, as industries have transitioned from analog and pneumatic to digitalized controls, sensor-based data has been key to lowering industrial operating costs, reducing risk and managing asset lifecycles. In today’s operating environments, IIoT’s pervasive sensor technologies along with improved connectivity and real-time analytics promise to expand the impact of operational data by closing information gaps, sharpening insight and creating new business models.
  Key Performance Indicators should work for you, not the other way around! By utilizing a real-time performance management system as the basis for KPIs and scorecards, progressive companies enhance their competitive advantage and improve the overall decision-making across an entire enterprise.
  Making the Business Case: Increasing Profitability with OSIsofts PI System in the Food & Beverage Industry The food and beverage industries are characterized by large numbers of plants with diverse information systems, stringent manufacturing conditions, thin operating margins, and increasing regulatory requirements. Driven by globalization, consolidation, and the need to reduce time-to-market, the complexity of the industry's manufacturing environment requires agility based on real-time information.
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