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Xbar control chart12/28/2022 Demand on human resource, funds for reagents and other consumables, high equipment utilization rate and repair, administrative burdens (documentation, quality control) are among the effects of high SIF to the FSL management. Higher SIF to FSL affects the sample management process. #Xbar control chart seriesThis paper focuses on the statistical time series analysis techniques on SIF data and introduces application of x-bar control chart technique as a tool for identifying uncommon occurrences of high sample influx so that causes can be identified and action can be taken to keep the sample management process under control. The SIF data shows strong variations with time, from case file to another and among the three disciplines, posing a challenge to the FSL performance. Currently, the FSL has undertaken studies to debottleneck the challenges including extended turnaround time (TAT), large number of case files submitted, large number of evidence or samples submitted per case file, defined in this study as sample influx data, financial and administrative hurdles, and human resource challenges. The FSL studied is part of a dynamic multi-disciplinary organization devoted to the ideals of excellence that provides leadership to advance forensic science and its application to the police investigation unit and legal system and other services offered by the organization. Currently, the sample influx is overwhelming, which require statistical analysis and decision making. Science applied at the scene can generate data for later analysis, provide quicker answers, and facilitate better analysis in the laboratory. The evidence received is viewed in the context of the crime, the persons involved, and the environment (both physical and temporal). All of the methods and processes employed at a crime scene are geared toward stopping the clock, i.e., keeping the scene and the evidence as much as it was when the crime was committed as possible until it can be recorded and documented. Crime scenes are the primary point of detection, collection, and preservation of evidence, before submission to the FSL. The FSL is the sole legally authorized laboratory to examine evidence submitted by any Governmental agency investigating a criminal offense. The forensic science laboratory (FSL) studied comprises of three disciplines (forensic biology and DNA, forensic chemistry and forensic toxicology), which receive, examine, analyze and reports on evidence submitted in criminal cases from all over Tanzania. Using this criterion, the rational subgroup range was established to be 4 ≤ k ≤ 20 for the two x-bar control chart rules. The goodness of fit was established to be the new criteria for rational subgroup-size range, for Rules #5 and #4 only, which involve a count of 6 consecutive points decreasing and 8 consecutive points above the selected control limit ( σ/3 above the grand mean), respectively. The variation of number of out-of-control points or violations, N ocp, for different control-charts rules with increasing k was determined to follow a decaying exponential function, N ocp = Ae – α, for which, the goodness of fit was established, and the R 2 value approached unity for Rule #4 and #5 only. For each value of k, a complete series of average values, Q( p), of specific length, N sg, was created from which statistical analysis was conducted and compared to the original SIF data, S( t). #Xbar control chart codeA computer code was implemented using a FORTRAN code to create x-bar control-charts and capture OCP and other control-chart characteristics with increasing k from 2 to 25. A sensitivity analysis on the N ocp was applied for subgroup size, k, and number of sigma above the mean value to determine the upper control limit, UCL x. Multi-rules were used to identify the number of out-of-control-points, N ocp as violations using five control chart rules applied separately. The characteristics studied include changes in out-or-control points (OCP), upper control limit UCL x, and zonal demarcations. This paper analyzes the effect of subgroup size on the x-bar chart characteristics using sample influx (SIF) into forensic science laboratory (FSL).
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