Issues and Directions in • • • • • • • • • • • • • • • • • • • • • • Laboratory Automation Joseph G. Liscouski
Research Computing Strategy (RCS)
Develop an RCS that will give you a rationale and structure for computer system planning
Implementation plan
Define a plan for each laboratory based on the RCS that will yield an integrated system
Tools
Use that plan as a guide for purchasing, developing, and using products
Digital Equipment Corp. Marlboro, Mass. 01752
Previous A/C INTERFACE articles have reviewed the technologies that will help us change and improve the chemistry laboratory. Having facilities available to us is one thing; understanding how to use and manage them is quite another. New technology will have an impact on how we work, what our workplace will be like, and the work we do. This article will examine some of the current issues raised by the application of automation systems to the laboratory. Computers, robotics, and networks may or may not play a significant role in your laboratory at the moment, but there is no doubt that they will in the very near future. Organizational issues
The introduction of a computer system into a laboratory represents both an opportunity and an agent for change. Will the computer system become just an electronic substitute for the paper system that you are currently using, or will it be used to improve the way your organization functions? We must identify the needs and key objectives that the computer automation system is going to satisfy. To do this we must develop a corporate-wide research computing strategy (RCS). In Digital's approach to laboratory and scientific computing (Computer Integrated Research), the RCS is part of a three-part process that aids in planning and implementing lab automation projects,
im, mplementation plan
ess flow
Figure 1. Research computing strategy for planning and implementing laboratory automation.
A/C
INTERFACE
as shown in Figure 1. The strategy should be the same for all scientific applications and laboratories within a particular organization. Differences between lab groups (e.g., basic research vs. an analytical laboratory) are reflected in how the strategy is implemented and in the actual products or tools used (Figure 2). The primary responsibility for the formation of strategies lies with the laboratory personnel and management, but it should be done in conjunction with corporate computer groups. The coopera-
Analytical and service (testing) labs
Basic and applied research
Research Computing Strategy (RCS) Figure 2.
Implementation of a research computing strategy.
0003-2700/88/0360-095 A/$01.50/0 © 1988 American Chemical Society
tion of the computer group is important because issues of support, maintenance, networks, system compatibility, and growth must be addressed. The primary benefits of planning include better understanding of overall requirements, a basis for communicating and comparing approaches between scientific and corporate computing groups, the ability to show how each part of the system will contribute to the automation plan, avoidance of premature obsolescence of systems, and improved support from higher levels of management (which will make the plans easier to implement). Setting goals to meet needs and objectives is the first stage in strategy development. Frequently the goals that first come to mind are improving productivity, providing more accurate results, and removing the tedium from routine portions of laboratory work. In addition, some other goals can be suggested, such as improving your ability to manage and work with data, information, and knowledge; providing an integrated hardware and software system within the laboratory; and improving the ability of your laboratory to
ANALYTICAL CHEMISTRY, VOL. 60, NO. 2, JANUARY 15, 1988 · 95 A
Knowledge (test methods) Information (sample management system) Data analysis software
3
Data hromatogram sto
Data acquisition software Figure 3. grams.
Databases and software package for collecting and analyzing chromato-
work with the rest of your organization. The products of analytical laboratories are information and knowledge. These products and the data on which they are based represent a valuable asset to your group and your company and should be properly managed so that you derive the maximum benefit from them. This management should require that data be stored in a way that makes it accessible and prevents it from being lost. Integration is a highly desirable attribute of any system. Providing for integration in a strategy designed to cover a broad range of applications can be difficult, particularly when you are working with products from a variety of sources. We can use the management of data, information, and knowledge as a means of testing for integration. First, we need to establish some definitions. Data refers to the measurements we obtain from instruments, including both individual measurements (such as weights) and collections (such as spectra and chromatograms). Information consists of statements or conclusions based on that data, such as the amount of antioxidant in a polymer. Knowledge is what we use (e..g, test methods) to produce and interpret the data. Note that these definitions will change as you move from one type of laboratory or group to another; information (e.g., the amount of antioxidant) to one group may be a data point to another group (e.g., process control). Information, data, and knowledge can be viewed as separate collections or databases. Applications software provides a means of taking an element from one database, working with it, and then storing it somewhere. Although this approach may seem a bit academic, it does have some ramifications when we consider integration in a laboratory system.
Figure 3 shows the three databases and a software package for collecting and analyzing chromatograms. If the data analysis package cannot be used to insert results into the sample management system, then we do not have an integrated system. To achieve integration, additional software must be written either by the supplier or by you. When implementing the system you might consider the following questions. Once data are collected, what tools will allow me to analyze and synthesize information? Do those tools have the ability to read the data and store the results in a sample management-tracking database? If I capture my knowledge in the form of test methods, reports, and papers, will the available tools (e.g., word processors) allow me to pull in supporting evidence and graphics? How does the system help me distribute my findings? Automation efforts can provide a substantial benefit to a particular lab-
Figure 4.
oratory. When the interactions between that lab and the groups they support or work with are taken into account, the benefits not only are greater, they are more likely to generate corporate support. Figure 4 shows some of the interactions that can occur in an organization. Each of these interactions is an opportunity to gain additional support for, and benefit from, a full lab automation project. For example, if the sample management system can electronically send results to a process control system, integration activities can expand outside the laboratory. Once the broad strategy has been set, the implementation plan must be developed. This is the time to establish your priorities. Few groups can afford to satisfy all their automation needs at once, and choices must be made between long- and short-term requirements. The key point to keep in mind is the ability to adapt to changes in priorities. Will the systems that satisfy your top priorities today be compatible with those installed later? Do they share a common base of communications? If you start with a smaller system for database work, can you expand to a larger one later without affecting your software system? Implementation
Once all of the necessary strategies and plans have been established, the next issue is the actual implementation of the system. Many chemists have be : come familiar with interfacing a particular instrument to a computer system, but that ability does not always translate directly into the ability to plan and implement a laboratory automation project. Even if your automation system is purchased as a turn-key system, it will still have to be maintained, have backup facilities provided, and have someone responsible for changes to the system.
Interactions within an organization.
96 A · ANALYTICAL CHEMISTRY, VOL. 60, NO. 2, JANUARY 15, 1988
Depending on the way in which the departments in your company work, some of this support may be provided by the computer services group. If so, this group will want to have considerable involvement in choosing the hardware and software and should fully understand and support your research computing strategy and implementation plans. If your company is considering the implementation of numerous lab automation programs, it would be worthwhile to put together a group of people responsible for those projects. This prevents each individual lab automation project from climbing the same learning curve. Although this method may mean retraining or adding people, the payback in smooth implementations, speed, and minimized total project cost will be worth the trouble. Knowledge and expertise in areas such as computer database design, communications networks, operating systems, languages, systems design, chemistry, laboratory instrumentation, robotics, and general systems theory, plus the ability to plan an automation project and then manage the implementation, are fundamental skills in "laboratory systems engineering." The people doing this work should evaluate the entire laboratory and plan a system that will permit growth and integration rather than provide a patchwork of incompatible solutions. These areas can be addressed by welldesigned graduate programs t h a t would substantially benefit the field. Part of your implementation effort should concern people in the laboratory. Do they understand what is being done and why? Are they part of the process in making decisions about automation? Hardware and software choices are only part of a successful implementation. If people fail to use the equipment or use it ineffectively, you will not realize the benefits that made the project attractive. Education can go a long way in training people to help make you successful. Although it is hard to avoid coming in contact with computers, some individuals are reluctant to work with them. Reasons for this reluctance vary. Some people may not understand the impact of the computer on their jobs; they may lack good typing skills; or they may be concerned about how to use the system, how it will fit into their routine, and what will happen if they make mistakes. Most of these concerns can be put to rest by providing a good in-house training program that familiarizes people with the technology and its impact on them. One company set up a formal training program on their sampling tracking system that allowed people to practice, learn, and make mistakes on a dummy database. This
approach built the necessary confidence and familiarity that encourage people to be successful. During these sessions, you will very likely get comments about things people like or dislike about the system, and these can be used to improve the system before it goes into production. Terminology It has been said that one purpose of an undergraduate education is to teach a new language: that of the specialty. Language assumes t h a t an agreedupon set of terms and definitions exists. Computer science and chemistry have met that requirement for a language; lab automation has not. We speak the same words (instrument interfacing, LIMS, networks, sample tracking, etc.), but with different frames of reference, and thus we attach different meanings to the words. Take the acronym LIMS, for laboratory information management system. What does it mean to you? I've listened to, and participated in, discussions of a LIMS system only to discover that each person had a different definition of what was meant. To some people it means a sample tracking system; to others it means everything concerning data and information handling in the laboratory, including capture, analysis, storage, management, documentation, and eventual distribution. The words sound like they should mean something, but the definition is highly subjective. Another ambiguous term is instrument interfacing. Before microprocessors became part of what is being sold as an instrument today, instrument interfacing usually meant connecting an analog signal from the instrument to a computer system and digitizing it. Now that processors are being sold as part of the package, much of what comes under the heading of instrument interfacing is really a problem in communications. Instruments that provide serial ASCII, IEEE-488, or BCD (binarycoded decimal) input and output require something—usually a microprocessor—to digitize the analog signal and then format it for output. The point of this is that you should define your interpretation of the terms before you use them and make sure that your audience (e.g., the budget review committee or the vendor) understands your requirements. The fact that you are asking for a LIMS system, and that three or four vendors have them, doesn't mean you have that many choices of comparable systems. The capabilities of various LIMS systems differ among vendors, and the list of features varies widely. Describe your needs according to the functions you want performed and the problems you want solved. Shopping for a LIMS sys-
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