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Visual Management
Published in Peter L. King, Lean for the Process Industries, 2019
The takt boards described display some of the most important metrics related to current production, specifically production to takt, deviations, and reasons for them. There are other metrics that are equally important and should be displayed just as prominently. These include quality results and trends, equipment reliability and trends, and the time to accomplish the most recent changeovers compared to the standard. Although some of these are lagging indicators and are not available in real time, they should be displayed as soon as they are available so people know how well performance standards are currently being met. It is also important for people to have a sense for whether performance is improving, stable, or declining, so trend lines are as important as the most recent values.
Forecasting in the air transport industry
Published in Bijan Vasigh, Ken Fleming, Thomas Tacker, Introduction to Air Transport Economics, 2018
Bijan Vasigh, Ken Fleming, Thomas Tacker
The fourth and final time-series method to be investigated is trend analysis. Scatter diagrams and line graphs provide a good first approximation in identifying the existence of a trend line between independent and dependent variables. Depending on how closely the points group together, we may be able to identify a trend in the data. Unfortunately, trends are not always easy to see graphically, and there may also be a problem with units. A more quantitative method to identify a trend line is regression analysis. Regression analysis attempts to create a linear trend equation to describe the data (Anderson, Sweeney and Williams, 2006). Such equations can then be used to provide a forecast for a future value. The general form for these equations follows: F
Aviation Forecasting and Regression Analysis
Published in Bijan Vasigh, Ken Fleming, Thomas Tacker, Introduction to Air Transport Economics, 2018
Bijan Vasigh, Ken Fleming, Thomas Tacker
Trend analysis The fourth and final time-series method to be investigated is trend analysis. Scatter diagrams and line graphs provide a good first approximation in identify the existence of a trend line between independent and dependent variables. Depending on how closely the points group together, we may be able to identify a trend in the data. Unfortunately, trends are not always easy to see graphically, and there may also be a problem with units. A more quantitative method to identify a trend line is to use regression analysis which attempts to create a linear trend equation to describe the data (Anderson,Sweeney, and Williams, 2006). Such equations can then be used to provide a forecast for a future value. The general form for these equations is as follows: Ft =bo+b1t
Study on the microseismic clouds induced by hydraulic fracturing
Published in Geomechanics and Geoengineering, 2021
Figure 8 shows the number of the activated NFs when HF propagates to different lengths. The model parameters are listed as in Table 1. We can see that the longer the HF propagates, the more NFs are activated. The number of the activated NFs increases with the HF length in an exponential way. However, only knowing about the number of the activated NFs is not enough to get a sense how they are distributed. In Figure 9, the distance of the furthest activated NF with the HF length is plotted. First, we plot the data points and then add a trend line. The trend line shows the distance of the furthest activated NF increases with the HF length. When the HF is short (e.g. less than 80 metres), the MS events are concentrated in a spatial domain close to the HF. This is consistent with the findings in Warpinski (2000) and (2001). However, when the HF propagates much longer, the MS events could spread very far away. The distance of the furthest activated NF does not increase so much when the HF length is very large (e.g. greater than 170 metres). The slope of the trend line decreases.
Radiation dose assessment of soil from Ijero Ekiti, Nigeria
Published in Cogent Engineering, 2019
M. R. Usikalu, P. P. Maleka, N. B. Ndlovu, S. Zongo, J. A. Achuka, T. J. Abodunrin
Figures 4 and 5 show the correlation of absorbed doses with the radium equivalent activity within the study areas. Regression analysis technique was used in drawing a trend line between the points. The regression correlation was positive, linear and high but higher in the control area than the mining area.