Feb 16, 2012
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| Figure 1. Inclusions in the steel of a car frame, as visualized using the Olympus BXiS microscope system and Olympus Stream software. At the center is a Type C/silicate inclusion; at the lower right is a Type D/globular oxide inclusion. Magnification: 100X. All images: Olympus America Inc. |
The tools used by industrial R&D departments must evolve quickly to keep up with rapidly changing technology. In the search for more cost-effective materials that maintain safety, automotive suppliers are working on advanced high-strength steels that use less material and reduce overall vehicle weight, while lowering manufacturing costs. Increased production efficiencies and higher performance demands are driving analysis techniques in textiles research. For example, defense contractors use durability analysis that involves measuring the open areas of the weave pattern while developing uniforms that protect soldiers from sun and sand.
To meet stringent specifications, R&D professionals gather material characteristics from testing and conduct measurements that reveal relevant performance information to support decisions about manufactured products. Sometimes, colleagues who are not familiar with the project must access, analyze, and make decisions on the data. All of this occurs in an environment where companies and institutions are cutting costs, using existing resources, and asking R&D engineers and scientists to work more efficiently.
As a result, industrial R&D organizations are changing the way they organize their R&D functions and train staff. Multinational companies are centralizing core R&D functions, but many organizations also are setting up small, entrepreneurial R&D/engineering areas for specialty research. This strategy encourages collaboration among engineers, improves economies of scale in equipment purchase and staffing, and stimulates innovative approaches to design and engineering challenges.
Training practices have been modified to prepare employees who may have specific skill sets but lack advanced degrees to make important contributions to the R&D process. To serve this workforce, tools have become easier to learn and use.
Reporting requirements have also changed. Data must be accessible, usable, and actionable, without the need for advanced interpretation. Previously, an operator would prepare the sample, adjust the microscope, and capture images of the relevant areas of interest, then, create a report with images using a word processing application. Formatting the report takes time; if the image was manipulated or resized, critical parameters such as the scale bar or integral metadata (calibration information, image acquisition data, etc.) could be lost or incorrectly displayed. Advanced imaging technology now allows the image metadata to be recalled and displayed on the image; the scale bar location can be resized and repositioned directly inside the report’s word processing application.
A tool for all users
Companies also have changed how they select and use equipment. Equipment purchased today must be easy to learn, with minimal training. Microscopes and image analysis systems—among the most complex tools used regularly in industrial R&D environments—are good examples of this change. Current tools and equipment must be simple for engineers or scientists to use to their fullest capability, even if the equipment is used only a few times a week. Users should be able to go to the microscope and acquire accurate results every time. Microscope controls and software features should be easy to use. And users should have the confidence that the results are accurate.
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| Figure 2. Microscope/digital imaging workstations, such as the Olympus BXiS microscope system, can help R&D professionals obtain critical analytical results. |
Imaging tools must balance automated features—so users don't have to go through multiple steps to get results—while maintaining flexibility to accommodate differing samples and parameters. Automotive R&D facilities are selecting tools that make it easier and faster to study changes in steel microstructures after exposure to high heat (Figure 1). Non-metallic inclusions embedded in steel during the manufacturing process previously were rated using a manual microscopic inspection protocol and a comparison chart. Now, inclusions can be detected and rated in accordance with international standards as a function of their intensity levels and morphological parameters. Moving this type of analysis to a digital format enables R&D facilities to increase throughput, minimize inconsistencies, and provide better documentation.
Traditionally, textile manufacturers examined the weave and composition of fibrous material under microscopes and captured images. Using an integrated microscope-image analysis system, fabrics can be examined, documented, and quantified. Operators define the objects or open areas to be detected; the system selects the objects and categorizes them by shape and size. While the earlier procedure involved multiple steps and subjective analysis, the new process is reduced to two or three mouse clicks.
As industry has ratcheted up performance demands on R&D organizations, it simultaneously instituted cost-cutting programs. For modern R&D organizations to thrive, they must look at functional reorganization; tools that require less training; reporting systems that deliver information in a readily actionable format; and accurate, reliable tools that maximize the time and efficiency of high-level R&D functions. In addition, integrated solutions—where the microscope, imaging system, instrument control software, and reporting tools all come from one company—can streamline service and training and establish a single-source of responsibility for the system's performance.
Source: R & D Magazine
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