- September 14, 2009
- PAS Inc.
September 14, 2009 - Integrity software from PAS not only automates the process but provides the means to capture the empirical knowledge stored both in paper-based documentation and in the minds of experienced automation professionals. Integrity builds on earlier generations of automated documentation systems developed by PAS including the widely accepted and acclaimed DOC3000 and DOC4000 systems for Honeywell DCSs. However, rather than being specific to one particular vendor or one class of systems, Integrity can capture data from any source. Moreover it’s not restricted to what would normally be regarded as automation assets but can capture knowledge from paper based and even human sources and handle it in essentially the same manner as that from electronic sources. Integrity provides a universal framework for aggregating and contextualizing data from across the entire process automation environment, irrespective of the individual source. It captures and archives explicit knowledge from each source, mapping the genealogy of the dataflow, and also provides a set of common search, query and reporting functions. Actually interfacing with and extracting data from the individual data sources is the task of a large and growing family of Asset Models. These driver-like plug-ins convert the source data into a common data format for the Integrity database. Currently more than 40 Asset Models are available, covering not only most popular DCSs, PLCs and safety systems but HMI/SCADA packages, historians and asset management packages. Attempting to capture and contextualize the knowledge embedded in today’s increasingly complex and multifaceted process automation environments has been likened to mapping the human genome. The systems managing and controlling today’s process plants are a closely integrated blend of ‘traditional’ measurement and control with applied IT, so much so, that many of the distinctions between the two and between the plant floor and the enterprise are blurring or even disappearing entirely. Up until now, however, the tools available to manage this sophisticated environment have focused on its individual components while largely ignoring their interdependencies and overall context, and this at a time when complexity is growing exponentially while resources, both in terms of finance and personnel, are becoming ever more constrained. Effective management of a plant’s automation assets is essential to the safety of its personnel and of its physical assets, as well as to ensuring consistent throughput while complying with an ever widening range of environmental regulations. Those automation assets include not just, at the field level, instrumentation, analyzers and final control elements, together with their associated instrumentation databases, and, at the control system level, a heterogeneous mix of Distributed Control Systems (DCSs), Programmable Logic Controllers (PLCs) and Safety Instrumented Systems (SISs), but, at higher levels, an ever expanding portfolio of advanced applications and production management packages. The installation and implementation of these assets involves an engineering investment many times greater than their original cost but, even then, their true value to the enterprise may only become apparent after an incident or when the empirical knowledge associated with them walks off the plant as experienced personnel leave or, more likely, retire. One leading US refiner recently reported losing 2500 man-years of operator experience through retirement at a single site in one year, while a major chemical company said that it expected to lose 75% of the operating staff at one of its largest plants through retirement by the end of the decade. Arguably the most important aspect of that ‘added value’ is the production knowledge which is embedded in a plant’s automation assets as a result of their configuration and operation. Such knowledge may range from process chemistry in the form of formulae and recipes to control strategies and automated procedures. It may also include the proprietary techniques from which an organization derives its competitive edge and the means by which it fulfills its environmental and safety responsibilities, in effect its ‘License to Operate’. Such knowledge is continually added to and refined over the life of a plant and results in its automation assets being worth significantly more at the end of their life than they were on the day they were installed. Clearly, for a process manufacturer, effective management of automation assets and the protection of the knowledge embodied in them are critical both to the effective day to day operation of the plant and to the retention of its critical intellectual property (IP). The former raises key issues of integration and interoperability, of change management and version control and of spares management and data recovery, while the latter requires the capture and contextualization of the knowledge held both in the heads of key personnel and in information systems and mountains of documentation. With plant automation systems having grown in complexity from a few hundred measurement points in the 1960s to a few hundred thousand today and process management applications often numbering 150 or more, it’s a challenge which has been likened to mapping the human genome, with the added complexity that the ‘Automation Genome’ is continually changing as a result of integration and interaction. It’s an analogy that stands up well under closer inspection. An automation asset has the equivalent of a ‘genetic’ structure in the form of its internal architecture and its external dependencies. Moreover those genetic structures differ from one asset class to another, be they field instrument databases, DCSs and PLCs or pure software assets such as historians or advanced process control (APC) or process management applications. However, such is the diversity and variety of these structures and their interdependencies that they can rapidly overwhelm conventional attempts to document them. What is needed, and needed increasingly urgently, is a solution which can ‘map’ a plant’s automation genome automatically and without human intervention. To do so it must be able to aggregate data from the different automation assets into a common system, give that data context by identifying relationships and hierarchies and hence simplify what are highly complex systems. That solution is now available in the form of Integrity from PAS. Integrity is modular providing scalability from base-level to higher level functionality. Integrity Essentials establishes the asset hierarchy, organizing data from the individual assets into a tree structure which enables drill down discovery of increasingly granular data. Meanwhile the complementary Reference Explorer exposes all of the automation references, supporting progressive exposure of the data, while Genome Mapping provides a third view of automation assets, generating a graphical block diagram of all automation relationships. Essentials also includes a Smart Links facility to connect text in Microsoft Office documents to the Integrity database, an Email Explorer which aggregates and contextualizes tagged emails in the Integrity database where they can be searched in context, a Defects Finder which automatically identifies ‘genetic defects’ or configuration errors and a Change Tracker which maintains a complete history of configuration changes. Spares Capacity maintains a central inventory, identifying spare hardware capacity, and allowing spares to be reserved against projects. Integrity Advanced Elements then provides a further degree of management capability in two key areas: Disaster Recovery providing a central backup and recovery resource, identifying the health of back up databases and providing a step by step recovery procedure on a system by system basis; and Integrity Loop Sheets, which integrates with Intergraph SmartPlant Instrumentation and provides integrated field and control strategy loop drawing, with automatic identification of discrepancies between instrument and control system databases.
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