Introduction to LabVIEW

LabVIEW (short for Laboratory Virtual Instrumentation Engineering Workbench) is a platform and development environment for a visual programming language from National Instruments. The graphical language is named “G”. Originally released for the Apple Macintosh in 1986, LabVIEW is commonly used for data acquisition, instrument control, and industrial automation on a variety of platforms including Microsoft Windows, various flavors of UNIX, Linux, and Mac OS X. The latest version of LabVIEW is version LabVIEW 2009 which was released in August 2009.

Dataflow Programming

The programming language used in LabVIEW, also referred to as G, is a dataflow programming language. Execution is determined by the structure of a graphical block diagram (the LV-source code) on which the programmer connects different function-nodes by drawing wires. These wires propagate variables and any node can execute as soon as all its input data become available. Since this might be the case for multiple nodes simultaneously, G is inherently capable of parallel execution. Multi-processing and multi-threading hardware is automatically exploited by the built-in scheduler, which multiplexes multiple OS threads over the nodes ready for execution.

Graphical Programming

LabVIEW ties the creation of user interfaces (called front panels) into the development cycle. LabVIEW programs/subroutines are called virtual instruments (VIs). Each VI has three components: a block diagram, a front panel, and a connector panel. The last is used to represent the VI in the block diagrams of other, calling VIs. Controls and indicators on the front panel allow an operator to input data into or extract data from a running virtual instrument. However, the front panel can also serve as a programmatic interface. Thus a virtual instrument can either be run as a program, with the front panel serving as a user interface, or, when dropped as a node onto the block diagram, the front panel defines the inputs and outputs for the given node through the connector pane. This implies each VI can be easily tested before being embedded as a subroutine into a larger program.

The graphical approach also allows non-programmers to build programs simply by dragging and dropping virtual representations of lab equipment with which they are already familiar. The LabVIEW programming environment, with the included examples and the documentation, makes it simple to create small applications. This is a benefit on one side, but there is also a certain danger of underestimating the expertise needed for good quality “G” programming. For complex algorithms or large-scale code, it is important that the programmer possess an extensive knowledge of the special LabVIEW syntax and the topology of its memory management. The most advanced LabVIEW development systems offer the possibility of building stand-alone applications. Furthermore, it is possible to create distributed applications, which communicate by a client/server scheme, and are therefore easier to implement due to the inherently parallel nature of G-code.

Benefits

One benefit of LabVIEW over other development environments is the extensive support for accessing instrumentation hardware. Drivers and abstraction layers for many different types of instruments and buses are included or are available for inclusion. These present themselves as graphical nodes. The abstraction layers offer standard software interfaces to communicate with hardware devices. The provided driver interfaces save program development time. The sales pitch of National Instruments is, therefore, that even people with limited coding experience can write programs and deploy test solutions in a reduced time frame when compared to more conventional or competing systems. A new hardware driver topology (DAQmxBase), which consists mainly of G-coded components with only a few register calls through NI Measurement Hardware DDK (Driver Development Kit) functions, provides platform independent hardware access to numerous data acquisition and instrumentation devices. The DAQmxBase driver is available for LabVIEW on Windows, Mac OS X and Linux platforms.

Role of LabVIEW Database in SPC Software

LabVIEW database allows for creating custom applications that interact with real world data or signals. In fields like manufacturing, engineering this is very beneficial, especially where the SPC Software is used. LabVIEW database as part of SPC software ensures that a higher quality is delivered where a process is concerned, in less time and fewer people involved.

It contains several components, a lot of which are necessary for any type of test, measurement or control application. These components include G Programming, hardware support, analysis and technical code libraries, technology abstraction, modes of computation, UI components and reporting tools. While SPC software helps maximize productivity of a process, LabVIEW in SPC Software ensures quick and easy use of the SPC software and also ensures faster processing of data and improve business productivity.

LabVIEW Database Connectivity Toolkit

LabVIEW offers an additional Toolkit called “LabVIEW Database Connectivity Toolkit”. With this toolkit you can communicate with different databases, such as SQL Server, Oracle, etc.

How IntraStage Can Help You?

IntraStage is middleware solution that seamlessly connects all of your LabVIEW testers, legacy testers, and manual entry stations into a centralized LabVIEW database. Once in the database, IntraStage provides off-the-shelf web reports for quality and yield, as well as exporting the data to tools like Excel, Minitab, and JMP.  IntraStage also easily ties into enterprise systems, such as ORACLE, SAP and other MES/ERP systems.  Now your internal team can develop test databases faster with IntraStage.

Product Quality Test Data generated by Automatic Test Equipment (ATE) in R&D, Manufacturing and Repair environments is no exception. The challenges of this enormous amount of Test Data is how to provide people with effective way to make product quality decisions from it. Quality today means augmenting the power of traditional SPC (Statistical Process Control) techniques with activities such as ensuring complete visibility into yields, being able to link failures with repair information and having a collaborative platform upon which all functions of an organization (R&D, Manufacturing, Supply Chain etc.) can access this Test Data to quickly root cause issues.

If you would like to know more about these trends and how some Fortune 1000 companies are improving their Product Quality our VP Sales & Marketing will be holding a seminar on…”Using BIG Data to Improve Product Quality for Electronic Manufacturers” at the FREE Del Mar Electronics & Design Show.

In 15 years, memory density will be 1000 times greater than today which is a peta-byte for 100 dollars. This can store about 85 years of video. A person will die before he finishes watching.”

- Eric Schmidt, Google CEO

Data is the lifeblood of any organization. With it, companies can understand current issues, analyze trends, and determine actionable results to provide superior products to their customers. Enterprise resource planning (ERP) and customer relationship management (CRM) systems have done this for the business intelligence world for many years. In the test and production arena, R&D departments are realizing that proper test data management can be a competitive differentiator in getting high-quality products to market faster. There is an increased need for a data management strategy, and if handled incorrectly, they can make test data a big problem.

Today, companies have a “build vs. buy” decision when seeking software solutions to manage product quality data in R&D, Manufacturing, Supplier or other areas of the product’s life cycle. As product quality becomes more and more important to retain customers, reduce operational cost and ensure customer satisfaction, it is no longer a decision on “if we need test data management”, but instead on “how should we implement quality test data management”.

As with everything, there is no single “correct answer” to this “build vs. buy” question. In this Blog, we will explore the needs of test data management and how to handle it effectively with the help of IntraStage SPC Software.

Studies show that in most of the companies up to 60 percent of application development and testing time is devoted to data-related tasks. Reducing time spent on test data management is critical in controlling IT costs and keeping developers focused on the task at hand – developing new applications and managing existing ones. To design and build reliable applications today, however, entails a complex process involving a range of different and unfamiliar databases and file types. Often, developers and testing teams spend more time dealing with data-related issues than developing the actual application itself.

Companies are inundated with data, and most are starting to realize that gigabytes of test data exist on hard drives throughout their supply chain. This data exists in a hodge-podge of formats, making it extremely difficult to normalize into a single database.  However, if this data were normalized, a number of macro-quality metrics would be possible, which could:

• Improve manufacturing yield
• Enable information visibility between functional groups such as R&D Manufacturing, etc to improve defect resolution times
• Optimize test times to move product through manufacturing faster
• Decrease warranty returns and recall events

Once a company has realized the positive financial impact that comes from better managing quality data, they often begin moving toward creating a normalized database and quality data management system. A common set of goals are:

1. Select a system that can scale throughout the enterprise and supply chain
2. Incorporate industry best practices
3. Finance with a “phase gate” approach, where a low-cost pilot project is proven successful as a step toward enterprise rollout
4. Deliver high value relative to TCO (total cost of ownership)
5. Leverage your company’s specific expertise and personnel

To select a system that can scale, the two core problems are:

1). How to build a robust data model that will work for all legacy test data as well as all future test data and

2). How to cost-effectively retrieve product quality test data from so many different locations, including those outside the firewall.

The good news is that several companies, including IntraStage, now offer COTS (commercial off-the-shelf) solutions for both of these core problems. For instance, rather than spending NRE (non-recurring engineering) dollars to create and debug your own data model and retrieval process, you can purchase this technology at a fraction of the cost of inventing it in-house.

Another benefit of using COTS technology is that the solution will already incorporate industry best practices, resolving goal #2. Rather than spending time learning all of the best practices and coding them internally, you can evaluate competitive COTS products and see how the best practices are coded into the product.

While most internal teams will agree that the above list of goals is a great “pie-in-the-sky” set of tasks, they will admit to being mired in issues of maintaining the existing systems. Some common issues that need to be managed include:

• How to maintain the system if a key developer or IT person leaves?
• How to add new feature requests from Users?
• How can system uptime be guaranteed to 99.99%?
• How to manage new applications to access the data?
• How to efficiently scale the system to add new users, new products etc?

These are areas where IntraStage can help.

The IntraStage solution offers a core foundation technology, solving the issues of data model, data retrieval, and out-of-the-box reporting while allowing your company to plug-in custom software and solve your specific needs for reporting, visualizations, and process around the test data.

IntraStage is a Quality Test Data Management Software provider for companies who design and manufacture electronic products. We provide SPC, Yield, CP, CPK, and test data analytical tools by automating the retrieval, storage, mining and reporting of R&D, Manufacturing, Supplier and Field test data. Our clients choose us because we seamlessly integrate test data from different sources, lower their product design, manufacture and return costs by finding quality trends more quickly and accurately. IntraStage’s test data management software that saves time and reduces the level of complexity often associated with managing distributed data and preparing data for testing.

IntraStage test data management tool simplifies the complex task of managing test data. Equipped with an easy-to-use graphical interface, IntraStage allows developers and testing teams to perform all data-related tasks without writing programs or scripts, coding databases or using multiple utilities. IntraStage provides a standardized approach to managing data from multiple databases and file types, gives users the tools they need to effectively work with data and increases productivity, all without prerequisite training or expertise. IT organizations will immediately save time and reduce costs using IntraStage in their development and testing processes.

Fortune 1000 companies rely on IntraStage’s business intelligence to keep them competitive when product quality and customer satisfaction are key differentiators. IntraStage product offerings ranges from on-site audits all the way to enterprise-wide business intelligence solutions. We can work with your internal team to build a quality test data management system that solves today’s problems and scales into the future.

Contact IntraStage today to get a proposal for a pilot project in your test department.

Test and Measurement World will announce the category winners at their Best in Test event, which will be held on January 31 in conjunction with DesignCon 2013; they will also announce them at www.tmworld.com in February. We hope to see you there!

With some careful planning, the test data collected from TestStand Database can be full of rich insights if some standard tags are added to the overall Test Data format. By standardizing on an output like Extensible Markup Language (XML), Automatic Test Markup Language (ATML) etc the re-invention of formats is eliminated. As the saying goes “Data is useless unless it is acted upon”. Test Data is key to identifying cost and throughput drivers on the product line. These new insights and capabilities can include Test Equipment Utilization, Test Equipment Accuracy, Yield Root Cause drill downs and Statistical Process Control (SPC).

With IntraStage you can seamlessly integrate test data from different sources and lower your product design, manufacturing and return costs by finding quality trends quickly and accurately.

IntraStage empowers businesses to make critical decisions easily and quickly throughout the product development life cycle with its Statistical Process Control Software. It has proved invaluable in uncovering improvement opportunities in both product design and manufacturing processes. Using a web based interface, IntraStage provides immediate access to all of your test data enabling you to quickly identify trends, failure analysis and yields. Built in QA routines such as CP, CPK, SPC and Six-Sigma help you identify the main issues affecting product quality.

IntraStage has no limit to the number of users who can take advantage of managing and analyzing their Labview database, from development engineers’ right through to manufacturing managers. By automating the process of collecting test data, OEMs can mine the data better and have the real-time SPC capability to view issues and respond quicker to potential problem spots. Due to real time and historical access to all your product test data you can visualize trends, SPC data which means to reduce product rework, retest, test cycles and bring faster response to complex hidden product problems.

Having deployed IntraStage you can achieve some meaningful results from the Test Data Tags implemented. Now it has become clear that with IntraStage’s Statistical Process Control Software we can do Intelligent Data Analysis and increase the quality of engineering decisions. Start using IntraStage today and improve your capabilities and reliability of the test data collection and statistical process analysis.

Statistical Process Control is an analytical decision making tool paramount for any manufacturing or engineering company to improve product quality by reducing process variation. It is a powerful tool that assists you to identify potential problems in process control and helps to optimize process, reduce process cost and observe noticeable improvement on the bottom line. SPC applies statistical methods and enables you to understand the interaction between variables, allow you to predict the effect of a new strategy and helps minimize the need for expensive and time consuming off-line testing.

Quality is a critical part in manufacturing line, crucial for every business because good quality helps to determine a firm’s success in a number of ways such as customer retention, well-built brand status besides attracting and retaining skilled workforce. Quality control and development department uses various tools to identify the main issues that affect product quality and acts to streamline quality by implementing corrective actions that increase productivity and maximize growth.

Studies reveal that SPC is well-known methods followed for monitoring, controlling and improving the process through statistical analysis. Manufacturers who have a continuous improvement program in place adopt Web Based SPC Software to monitor and control process variations and prevent waste from occurring. Every organization has number of processes and variables that can affect product and service outcomes, one greatest challenge is find & focus the processes & variables that are of key importance.

SPC tools help identify areas that need attention, but managerial approach is required to use the SPC tools well. SPC Software guides you the type of action that is appropriate for improving the functioning of a process, analyze the return on investment and aid industries follow data-driven philosophy of quality improvement that values defect prevention over defect detection.

SPC Software has number of tools to evaluate processes. Using the right tool will give you the exact Data Reporting of the process. Data reporting of each process is shown in chart format. Control charts graphically display your process information in an intelligent manner to operators and managers. Different types of charts like control chart, flow chart, Pareto Charts, Cross-sectional Chart, Mean chart, CUSUM and EWMA Charts and g Chart determines the ability of a process to meet client specifications. Leverage on Intrastage’s software to integrate test data from different sources and develop plans that directly impact the bottom-line.

• Why Traceability and Compliance are getting more important
• Test Data and Database Best Practices
• Demo of using IntraStage to rapidly look up Serial Numbers and pinpoint failure causes
  We also have a whitepaper available on Compliance & Traceability.  Check it out!

What is Statistical Process Control (SPC)?

Statistical process control (SPC) is a systematic decision making tool which uses statistical-based techniques to monitor and control a process to advance the quality or uniformity of the output of a process – usually a manufacturing process. It is commonly used in industry to measure the productivity or to measure, track and improve the ongoing performance of a process or determine if the process is in control or not. The significance of SPC Software is that by monitoring the process and bringing the process under statistical control to identify and take action on special causes of variation. SPC is supportive to maximize the overall profit by improving product quality, improving productivity, streamlining process, improving customer service, etc.

What are steps involved in using Statistical Process Control (SPC)?

• Plan: First identify the root cause of the problem and take corrective action to that problem. A corrective action is an immediate action as soon as the problem is identified.
• Experiment / Research: When problem occurs SPC software helps to analyze and empowers you to make better engineering decisions easily and quickly throughout the product development life cycle.
• Analyze: With the help of digitalized test data have a complete view of the manufacturing metrics and try to spell out all of the possible issues and send the data to R&D thereby improving product quality and customer satisfaction.
• Act: If the result is successful then work on additional improvements. If the result is not yet successful then the look for other ways to change the process.

Specifically About Control Charts

Process control charts are just about simple-looking connected-point charts. The points are plotted on an x/y axis with the x-axis usually representing time. The plotted points are usually averages of subgroups and they can also be individual measurements. SPC control charts exactly shows the merits and demerits points of each process in a graphic format. Control charts help to identify the difference in a measurement during the time period that the process is observed. More importantly, the chart will show you how the process is performing and how the process capabilities are affected by changes to the process. Also, identify bottlenecks, waiting times, and other sources of delays within the process. Finally, SPC over other methods of quality control such as “inspection” is that it helps to maintain the consistency of a process, which will result in a consistency in the quality as well.

Control charting is vital steps involved in distinguishing between common cause variation that is always present and special cause variation that is out of statistical control. Statistical Process Control technique steps include detection, study, prioritization, illumination and then charting. Before using quality control software collect proper data for analysis. Consider first quality is a sequence of continuous improvement. This control charting procedures is greatly assisted by SPC software like IntraStage.

Ready to give IntraStage a spin? IntraStage offers industry’s leading real-time SPC software for better and faster engineering decisions. It automates data collection and analysis on the manufacturing plant floor, allowing you to prevent defects before they occur. Start saving time, money and systematically improve quality and efficiency.

Today the most dominant sensor for getting Test Data on Electronic Products in manufacturing environments is through ATEs (Automatic Test Equipment). At IntraStage though, probably 90% of our customers also have some Stations in manufacturing whether repair, manual assembly stations etc.. where an ATE is not feasible or required. What happens at these Manufacturing Stations is that some operation is performed on the product and then a small number of Test Data is recorded on Paper.

While this is good that the Test Data is actually being recorded on paper..what is difficult about this situation is not having the ability to quickly aggregate and mine the Test Data to determine true Yields, SPC, Rework etc. Having a stack of paper located in some filing cabinet always seem to de-motivate people to do that…go figure.

No longer is this a necessary situation though..web based technology can solve this problem by allowing Test Data to be directly recorded in Paperless Web based forms. While this adoption has been slow…we feel that it is inevitable that all Test Data will be digitized..and only then will the Company have a complete view of its manufacturing metrics like yield, rework, scrap etc.