An architecture for consolidating metrology information islands typically involves a more complex and sophisticated infrastructure, including a Web-based front end for anytime, anywhere access; the ability to handle a wide range of tasks beyond calibration, including repair, preventive maintenance, proof load and inspection, and other useful features such as real-time status tracking, structured history and procedures databases, and automatic e-mail alerts for recall, delinquency or out-of-tolerance notices. Source: AssetSmart
While much has been written about calibration software, relatively less literature exists concerning the relationship of metrology services to the enterprise and better ways of connecting metrology information and services to the equipment operators.
There is a three-phased approach for improving this interface:
Integrating disconnected calibration information islands into a more cost-effective consolidated enterprise metrology services system.
Establishing a common data set of equipment tracking and management attributes with the business units and organizations that deploy the equipment to improve recall and status tracking processes.
Standardizing equipment descriptions across the enterprise to provide a common language for describing test and measurement assets.
The phases can be implemented concurrently or one phase at a time. All of them involve either higher levels of information integration or standardization of the information attributes used to administer metrology and equipment management functions and processes across the enterprise.
There are several dimensions of integration, including vertical integration between active lifecycle functions, horizontal integration over the time axis and organizational integration across the enterprise-and each must be addressed in a comprehensive solution.
In all of these dimensions, the goal should be to guide the calibration services function away from becoming an island. For example, the calibration recall function must know the current location, status, responsible organization and contact individual in order to seamlessly and efficiently issue recall notices.
In the absence of effective integration-all too often in real life-keeping track of these simple connections can cause a lot of wasteful activity. The following discussion highlights ways to improve these connections.
Connecting the Dots
The history of information management revolves around achieving ever higher levels of information integration where quality functions that were once fragmented across disconnected sites have been and are being combined into more highly integrated knowledge bases. However, calibration management software has lagged behind the general trend, and many isolated islands still remain, whether in the sense of having a limited functionality, being confined in their reach to a single location or facility, or residing on obsolete computer platforms or databases that lack vital security and integrity capabilities.An architecture for consolidating metrology information islands typically involves a more complex and sophisticated infrastructure, including a Web-based front end for anytime, anywhere access; the ability to handle a wide range of tasks beyond calibration, including repair, preventive maintenance, proof load and inspection, and other useful features, such as real-time status tracking, structured history and procedures databases, and automatic e-mail alerts for recall, delinquency or out-of-tolerance notices.
Further capabilities specific to the metrology function include database partitioning so that metrology service providers at each separate location or business unit have exclusive access and control over their own data; support for in-house as well as tracking outsourced vendor-performed services; a generalized application programming interface to facilitate import of results data from so-called benchtop systems and automatic calibrators into a single history repository; interactive capture of readings data and automatic flagging of out-of-tolerance conditions.
Of course, key to the success of this model is the underlying database, which must provide full data integrity, full commit-rollback features and automatic backup to ensure that no data gets lost. The structure of the database also must be able to impose order on how and what data is entered and ensure that the same types of events are recorded in a consistent manner.
Thus, table-driven validation of all crucial data attributes, such as technician IDs, condition or result codes, and accounting charge numbers needs to be combined with an unlimited, structured, history database (as opposed to free-form text notes), to capture labor, environmental test conditions, parts/materials used, standards traceability and readings data in the form of individually defined discrete data attributes.
Obviously, the ability to share data is particularly important in enterprises where members of the quality or metrology teams may be scattered in several different geographic locations. At the same time, a system that allows internal customers to help themselves rather than relying on the quality department or metrology staff for generic types of requests also can make a huge difference in productivity.
Such features would include integral service request and work backlog management tools accessible over the Web, as well as hooks to digital media documents so that a manufacturer’s calibration procedures and other manuals may be accessed electronically.
For quality managers, key features would include real-time status tracking and externally defined (tabled) workflow logic for total visibility over jobs, equipment, technicians and vendors, not to mention security features to manage and control user roles and access to transactions and data functions, with a role-oriented transaction structure to facilitate smooth and complete work in process operational flow.
Common Tracking Data
All too often audits reveal that data definitions and values for the tracking of instruments and equipment are inadequately controlled and at variance with those used by a company’s accounting or property departments. This is counterproductive to achieving an efficient customer interface, which should not have to deal with different records systems in order to track its resources.The need for a common language is particularly critical in more modern open enterprise systems wherein the customer is empowered to inquire on and make selected updates to his equipment data. The technical solution is straight forward-simply define a common set of tracking attributes and establish validation tables and logic to enforce the values.
Validation tables may contain basic data attributes, such as a responsible employee code and name, or may exist in more sophisticated forms called reference tables. For example, a more complete employee reference table also might contain first and last name, departments, home address, telephone numbers and e-mail addresses.
Structured Cataloging
Equipment cataloging is a value-added process that standardizes and structures asset descriptive attributes into consistent formats and values and automatically combines attribute data into useful management information so as to enhance asset and metrology management processes.Modern computer search algorithms and languages such as SQL can obviously search for instruments by descriptive attributes, such as manufacturers, model numbers and descriptions in any database. However, unless the data is first accurately structured and normalized in the database, searches are likely to be slow, nonintuitive, incomplete and unreliable, particularly as inventory volume grows beyond a few thousand items. Structured cataloging methodology was invented to solve this problem some number of years ago.
The human-to-computer interface works most cost-effectively when equipment data formats are current, consistent, complete and in a natural operator language format, as opposed to cryptic codes, which must be interpreted and translated, and therefore are not as user-friendly.
The human interface is equally unreliable in manually administering consistent descriptive attributes in equipment databases over a long time span of months or years. While legions of computer classification code schemes have been attempted over the years to help solve the problem, none of them have ever met all of the necessary requirements.
Many organizations attempt to solve the problem via brute force, by assigning analysts to continually revalidate and manually sanitize the asset records, often relying on endless physical inventories and paperwork audits to support this costly and futile effort.
Others attempt to use one or another of numerous classification and coding systems that are in existence across industry and government. However, these codes can only provide a unidimensional categorization of assets-whether by manufacturer, product type or model number-but are generally incapable of describing assets in terms of multiple attributes.
For metrology or equipment management purposes, single-dimension classification codes are of limited value. At a minimum, a three-level configuration is required. Since calibration requires detailed procedures and tolerance specifications, normally oriented by the manufacturer and model of the device, these two attributes plus a standard noun description would typically comprise a primary three-level coding structure.
But, because humans require lookup tables for codes, a more sophisticated and operator-friendly approach involves building a database dictionary where the attributes are automatically combined into operator-friendly relationships by database linkages. For example, a typical output defining a discrete model would look like this:
MULTIMETER, DIGITAL - - AGILENT - - 3458A
Since there is ideally a unique reference code defining these relationships, entry of the code automatically drives the relationship and may be used to reference unlimited external documents and related data sets such as calibration procedures, manufacturers’ manuals and calibration history.It is essential to metrology quality that all instrument or equipment models be tied to the proper procedures and history data and vice versa. Ideally these key data attributes become standardized across every use in the enterprise system.
The three-attribute design may be extended into an even more interesting five-level structure where performance specification data may be attached to equipment models in the catalog dictionary. These added dimensions provide two important capabilities.
First, the attributes are defined in metadata relationships as separate defined data entities. Once implemented, the performance attribute capability enables an automated side-by-side comparison of operational characteristics for different models of equipment-a typical equipment management search request.
Further, multifunction or reconfigurable products may be cross-referenced across multiple noun and performance families. For instance, a search for voltmeters will typically turn up multimeters having the equivalent selectable function.
Structured cataloging, when coupled with other equipment management tools, such as life-cycle replacement planning and equipment rental pools, can reduce annual capital expenditures for test and measuring equipment by as much as 10%.
Structured cataloging turns an otherwise ordinary asset database into an operational tool that enables operators to locate needed in-house resources in a few seconds, thereby speeding up technical projects. Equipment requests can be easily and quickly matched up with redeployable assets available elsewhere in the organization.
Properly done, cataloging enables operators to participate in a single easy-to-use enterprise system, rather than laboriously creating duplicative records systems on their desktop PCs.
For enterprise metrology purposes, structured cataloging allows recall template records, procedures databases and quality history data to be precisely organized by manufacturer, mode and standard noun description, thereby eliminating unnecessary duplication of records, speeding up setup time for new items and enhancing the accuracy and precision of quality metrics.
BENEFITS
Most companies have long since standardized and consolidated their accounting, HR and manufacturing information functions into so-called enterprise resource planning systems. Very few modern companies today would consider running their separate business units with disparate accounting systems that could not efficiently communicate with one another.For all the same reasons, they have every incentive to consolidate and integrate their calibration and equipment management operational systems. In doing so, they can improve their ability to maintain frequent and continuing close coordination between metrology services, equipment management processes and customer operational requirements.
The use of standard systems and information likewise speeds up support for projects and processes being supported. But the benefits do not stop there.
As regulatory standards become more stringent and complex, a single-controlled information structure makes complying with regulations infinitely more efficient than trying to work with disparate computer data bases and hardware.
Finally, consolidating information for metrology and equipment tracking into a single structured catalogued asset database will help reduce costs. A unified, integrated system can eliminate duplication of information systems and functions, enable widely separated team members to work together more effectively with less face time, and reduce redundant investment in duplicate equipment and resources.
