Industrial Intelligence Delivering Performance Information from Real Time Production Data

Transcription

1 Industrial Intelligence Delivering Performance Information from Real Time Production Data Tom Muth & Elliott Middleton Wonderware/Invensys Systems

2 Strana 2 Introduction Every manufacturing company gathers and dutifully records millions of data items on its production processes. Usually this information is required for tracking product quality to meet regulatory requirements or to be able to respond to product recalls, etc. All too often, however, this information is not used effectively to optimize the production process itself. This use of data is now regarded as a new class of industrial intelligence that can be extremely valuable in detecting events and trends that can be analyzed to improve production. No company can improve what it can t measure but by properly delivering industrial intelligence, a plant s operators, process engineers and managers can now easily answer questions about complex manufacturing operations that will allow them to streamline production to deliver higher product quality and reduce manufacturing costs. This paper will review the unique combination of analysis tools available from Wonderware that allow anufacturers to create and deliver this industrial intelligence. This new data is gathered at the supervisory control layer and provided to all users in a plant or in a company via web browser portals so that the cost of delivery is minimal but the power of its analysis has maximum impact on operational effectiveness. Myriad Data Sources Most companies have plant manufacturing data dispersed throughout their facilities in multiple systems sources, from production lines to laboratories, maintenance, scheduling, business and enterprise systems. The problem lies in the fact that each of these systems is independent and there is little interaction, if any, with other applications. This creates an often unrecognized dilemma in that data required to make proper decisions within any of these applications is incomplete without corresponding data from other systems. As an example, it s difficult to maintain smooth scheduling of product deliveries when there s a breakdown on the manufacturing line. Each application tracks data relevant to its own requirements, but all too often, that data is navailable to other people who can make good use of it. This results in decision-making that is less than ideal and it occurs at every level within a manufacturing environment, because the more complex a process is, the more difficult it is for one person to stand in one place in a plant and realize what s going on, much less understand the ramifications of it all. How can a company resolve this dilemma? Basically all the production data from the plant floor has been collected in the plant data historian, but it s rarely used as the basis for making business decisions. There s no use of this data as industrial intelligence that can enhance the performance of the plant processes. In essence, there s a gap between the world of supervisory control, at the operator level, and the world of enterprise applications, at the plant and corporate management levels. Changing this situation isn t as difficult as one might think. All it takes is to deploy analysis tools that are readily available, such as several FactorySuite applications available from the Wonderware software unit of Invensys Systems, Inc. These include: the IndustrialSQL Server real-time relational database the ActiveFactory reporting and analysis toolset the DT Analyst downtime reporting and analysis package the QI Analyst real-time, online statistical process and quality control (SPC/SQC) package and the SuiteVoyager industrial strength web portal that provides access to data via the Internet or corporate intranets using industry standard browser software such as Microsoft s Internet Explorer. Various combinations of these FactorySuite supplementary applications can provide all the capability needed for any manufacturer to implement a complete industrial intelligence solution and at a far lower cost than has previously been possible. Where it used to cost as much as $500,000 to implement a highly engineered solution, these off-the-shelf tools are available to do the same job at a fraction of the cost. And their ease of use means that expensive experts aren t required to implement them. In most cases, they offer point-and-click simplicity of setup and use, and the collection and presentation of data in the browser can easily be customized by the user. For example, SuiteVoyager provides access to data from numerous sources and IndustrialSQL Server integrates easily with any relational database.

3 Strana 3 Industrial Intelligence Role-Players IndustrialSQL Server IndustrialSQL Server is a critical piece of the equation for intelligence uses simply because it s a high performance repository for all production data. It gathers data from production systems and devices in large volumes and at high speed, then compresses the data for more efficient storage in PC-based systems. Because it s based on Microsoft s SQL Server 2000 database, however, data is accessible like any other relational database via structured query language (SQL) statements and is fully compatible with most IT departments standard database applications. Part of the power of IndustrialSQL Server is that it stores not only data measurements, such as temperatures, flows, counts, etc., but it also captures event information. This is critical for putting process data into the context of business decisions. As an example, the factoid Tank Level=0 is a piece of data that tells anyone that a tank is empty. But that data can also represent an event, such as the completion of a batch, which is important to know. Or it might represent the fact that a bulk tank of a necessary recipe ingredient is empty which can cause downtime for downstream equipment because they re starved of a raw material. As you can see, it s possible to overlay events on data to arrive at industrial intelligence. Another example: suppose you want to combine data from various departments so that operators can make choices on action items that will affect the current production process. Perhaps you d like to overlay lab quality test results on production data to guarantee that production is within control bounds. Most systems would require you to copy the lab data into the historian but IndustrialSQL Server can simply point to the lab system historical data and it can be captured and overlaid on the production data. This is a much easier approach and it s seamless from an end user standpoint. The same could be done with maintenance information, such as when an instrument was last calibrated, so that operators are sure the quality test results are valid. ActiveFactory Working hand-in-hand with the historian is the ActiveFactory reporting and trending package, which allows users to gather data and analyze it based on combinations of factors, then report production metrics in ways that facilitate their business analysis. As an example, one leading lumber mill has used this toolkit to analyze every step in a complex process to make oriented strand boards. Having so much good information on every step meant staff could review details and data trends that they never were able to see before. By treamlining the entire production line taking mere milliseconds off of the time needed to perform each of thousands of production steps they were able to remove as much as nine seconds off each production run. At a cost of hundreds of dollars per minute, this added up quickly and the IndustrialSQL Server and ActiveFactory software paid for itself very in two months. DT Analyst Similarly, the DT Analyst package provides many benefits for implementing intelligence features and is critical to achieving overall equipment effectiveness (OEE) in a production environment. Many applications that are claimed to be OEE solutions only provide data on a per-shift, daily or weekly basis. This level of detail is adequate for comparing performance, but wholly inadequate for uncovering the reason behind the differences if there were 30 reported downtime events during that period, they d all be rolled into one report with little or no visibility into the details of the individual events. DT Analyst is an online solution that provides downtime information on a real-time basis, as it s happening. It provides the granularity necessary to make business decisions on plant floor operations based on real equipment efficiencies. Once a piece of equipment has gone down, that event is recorded and detail is gathered on the root cause(s) of the downtime. Was it actually an equipment failure, or was the workstation starved for materials because of an upstream supply fault? If the line doesn t have in- ound product, it shuts down, and it may not have been an equipment failure but a lack of product. Or if it was an equipment failure, it may have been caused by an electrical problem, or a jam, or any of hundreds of potential failures. In addition to downtime due to failures, supervisors also can use a tool like DT Analyst to analyze variations in productivity from one line or shift to another and take corrective action to bring them all to a higher level.

4 Strana 4 The bottom line is, when examining operating equipment effectiveness from a business perspective, it s important to look at four factors: The fact that downtime occurred What the root cause of the downtime was The ripple effect of downtime, either up- or downstream The logic used to provide the detection rules Plant personnel may be able to tell that equipment has shut down because a counter stopped incrementing, for example. But to infer why the shutdown occurred may require looking at other variables. This logic can be placed anywhere and can be implemented using Visual Basic scripting or adding it to PLC logic. VB can result in fragmented logic and tracking, while DT Analyst provides an integrated approach that doesn t require programming at all. PLC programming can have unintended consequences, such as in the case of a pharmaceutical or food processing plant where it may impact on the validation of the process under control. A tool such as DT Analyst can easily be set up to track and report all of this data without any impact on validated processes. QI Analyst In similar fashion, the QI Analyst statistical process control package provides better than average benefits because it, too, operates in real time rather than offline mode. This application allows plant staff to modify processes as they are run, enhancing productivity in almost a closed loop fashion. The difference in online versus off line SPC is empowering operators to respond to process changes immediately and prevent significant quality problems rather than blindly continuing to make defective products for hours while waiting for feedback from the quality department or lab. QI Analyst also enables operators to distinguish true process changes from noise caused by inaccuracies in instrumentation, controls and raw materials which means operators need only respond to actual problems, not false alarms. As a good example of QI Analyst s power, consider a leading coffee producer that packages its coffee in cans at high speed. The problem was that coffee is sold by weight, but the can filling equipment was volumetric. Since the ground coffee density varies according to the particular blend, the system weighs each can as it comes off the filler machine and, if a statistically significant weight difference is detected by the SPC package, a calculation is made on-the-fly and a small applet responds to the SPC alarm to change the setpoint of the filler machine. It only addresses the signal change, not the noise. By better controlling the variability in can weights, the manufacturer is able to reduce lower the fill setpoint, give away less coffee and still meet the minimum package weight. Browser-Based Information Delivery Having all this industrial intelligence generated by applications like these is good, but it s not truly useful unless everyone who needs production performance information can access the data to do their jobs. SuiteVoyager That s where SuiteVoyager comes in. This is Wonderware s industrial strength portal software that serves as the delivery mechanism for industrial intelligence data. It provides access to the IndustrialSQL Server historian via a browser and users can customize the data they want to gather and present it in the most useful format for their work needs. It publishes the data across the web so that large numbers of people can access it, but each person can tailor its presentation and view it from multiple aspects. Each user has an individual dashboard that aggregates content and applications so the user can focus on the business decisions at hand without the delays and expense of relying on IT experts. As an example, consider a major electric power utility in the Midwest that uses SuiteVoyager and IndustrialSQL Server to aggregate data from three primary production applications coal yard operations, boiler management and turbine management to ensure that the company makes money with its generation processes. Their web-based performance monitoring system offers as many as 50 different SuiteVoyager screens that operators can monitor, allowing them to track and optimize the process in real time. This enables staff to maintain the balancing act in energy production that can make a huge difference in whether the company makes money.

5 Strana 5 For example, they can use some of the turbine steam to pre-heat the boiler water so steam production is enhanced. However, if they take too much steam off the turbine, it may reduce the volume of electricity being produced. And if they use only cold water in the boiler to make the steam, their fuel cost rises because they have to heat the water more. There s a point in the cycle at which they can optimize the levels of steam and heat energy without impacting power generation efficiency, and they get a big benefit in the boiler stage because they ve pre-heated the water before it enters the boiler. Being able to fine tune the process that closely truly makes a real difference in overall profitability. Having the ability to monitor multiple variables via SuiteVoyager is what makes it possible to achieve these results. Another nice feature is that each user is able to set the portal up for the way he or she wants to use it. There s no need for IT staff to get involved in this daily usage, yet IT management knows that SuiteVoyager is consistent with corporate technology standards. This helps relieve the load on overworked IT staff while removing any potential bottlenecks in data acquisition, reporting, trending and analysis for production staff. Summary Achieving true overall equipment effectiveness in a production environment can often be much like solving a simultaneous equation. There are so many variables involved, which are changing continuously, that plant staff cannot make realistic business decisions about production operations without the added value of tools such as those in the FactorySuite. There are three factors involved in OEE: Quality Availability Productivity These are generally considered as percentages: the percent of good product coming off the line, the percent of line uptime that s available at any given time, and the productivity as a percentage of rated capacity. Multiplying those three together determines a plant s OEE rating. Many manufacturers using these Wonderware solutions in one combination or another, depending on their production requirements, can see productivity ratings of about 40% climb by as much as 50% to a total production rating of 60% of capacity. That s a huge increase, and if the variability is that great, users can achieve improvements simply by determining the reasons for variations and making changes to processes. Successful repeatability can make a significant difference in overall profitability for a manufacturer which is of critical importance in these tough and competitive economic times.

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