Real-time machines types

The EZ-Track system can also be used to count good parts, diverted parts, packed cases, etc. Downtime is measured automatically and can be classified into an unlimited number of causes. Once production data is collected, there is an extensive set of Web-based reports that can incorporate trend charts, tabular reports, pie charts, and Pareto charts. Finally, it is possible to interface the EZ-Track system to ERP/MRP systems via an advanced SQL database that is open, fully documented, and ODBC-compliant. Not only is the EZ-Track system scalable from small to large numbers of molding machines and other types of cyclical manufacturing equipment, it also can play an important role in sending real-time production data to company-wide ERP/MRP systems. 

A data acquisition system was used to collect real time temperature, pressure, and position data for each cycle. A type J intrusive temperature probe having a diameter of 3.2mm was inserted into the machines nozzle to obtain melt temperature measurements. The radius of the nozzle bore was 6.4 mm and the probe protruded in by 3.2mm. Additionally, three type J thermocouples were used to monitor the steel temperature of the nozzle assembly. Figure 1 shows the nozzle assembly and the locations of the thermocouples. The data acquisition system was calibrated by submerging all of the thermocouples in boiling water and then adjusting the signal gains until each read 100 +/- 0.3°C. The recorded temperature data was filtered prior to data analysis. 

The author has often wondered how often machines are redesigned and rebuilt or even replaced for reasons that were later found to be incorrect. Based on observations over a considerable number of years, the number might be staggering. Ironically, the incorrect diagnosis sometimes results in a solution that will at least for the time being appear to fix the problem. This type of solution may possibly lead to a future problem because an incorrect symptom-cause relationship is established that will not hold true on another application at another time. All of this is being said to stress the need for proper and careful problem solving that accurately determines the real cause for the problem. It is difficult to address the common sense side of reliability and not make some type of... 

Unfortunately, several difficulties prohibit us from using this model to predict the operation cost. First, the cutter path is not known at the process-selection time. Generating a cutter path for each possible process to be machined would be very time consuming. The second problem is the availability of coefficients for each combination of tool-material type and workpiece-mateiial type. There is little published data for tool life equations. Most of the tool life and machinability data are published in terms of recommended feed and speed. With these two major problems, this approach will probably not work for real-world problems. A quick and dirty way must be found to estimate the cost. 

In this example the lead times that the firm proposes are accepted with a certain probability i4. The values of these probabilities have been given in the formulae (7.3.1) and (7.3.2). The normal available capacity on each machine will be 9 units. If no orders would be withdrawn and if we have one set-up on each machine every period, the machines would be occupied more than 90 percent (25 out of 27 units). Due to the withdrawals the real occupancy rate will be around 85 percent. For this example we will first make an arbitrary choice for the penalty points and for the additional elements. We start with ci = 3, D = 3 and mcl = 3. The 2 value is chosen arbitrarily as 2 =2 for all types and priorities. The choices for the other parameters are given in the matrix XQC. ... 

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