Introduction - industrialeblog



Cover PageTable of Contents TOC \o "1-3" \h \z \u Introduction PAGEREF _Toc444973603 \h 1Objectives PAGEREF _Toc444973604 \h 1Procedure PAGEREF _Toc444973605 \h 1Equipment PAGEREF _Toc444973606 \h 3Results PAGEREF _Toc444973607 \h 4Calculations PAGEREF _Toc444973608 \h 5Conclusion PAGEREF _Toc444973609 \h 11References PAGEREF _Toc444973610 \h 12Introduction This is the fourth lab report of human factor IE342. This report is about the Anthropometric Measurements of human body as one of related subject to human factor as well as vision and audition experiments on previous reports. Anthropometry is the measurement of people and the analyses of those measurements for various purposes like increasing capability of worker and makes the workplace more comfortable CITATION umt16 \l 1033 [1]. These measurements include all physical dimensions of the human body like: weight, height, waist,…etc. anthropometry plays an important role in industrial design, clothing design, ergonomics and architecture where statistical data about the distribution of body dimensions in the population are used to optimize product. Next sections will present the objectives and the procedure of this experiment, and discuss the results. Objectives The main objective of this experiment is:Understanding the uses of Anthropometric Measurements and its importance in industry.Understanding the correct method to collect the data of Anthropometric Measurements, and be familiar with tools that are using to measure.Understanding the way to analyze the data and comparing the results to the average results of human been in different area. Procedure The studied variables included 36 anthropometric parameters as well as some basic parameters including: age, ethnic origin, father’s occupation and family size; the latter two parameters may be used as indicators of the socioeconomic status, ethnic origin is an indicator for heredity. The studied parameters are showing in figure (1). The procedures of this lab. Exercise can be summarized in the following points: Students are divided into groups. Each group consists of two students. Each student of the two should take the 36 anthropometric measures of the other one and record them in the attached data collection form. The collected 36 anthropometric measures are assigned to the students so that each student will take one of the 36 anthropometric measures of the class to analyze it. The analysis includes: Testing the normality of each anthropometric measure. Calculating the 5th, 50th and 95th percentile. 2190756045200Figure SEQ Figure \* ARABIC 1 Anthropometric MeasurementsFigure SEQ Figure \* ARABIC 1 Anthropometric Measurements2190750Equipment The instruments used in this lab exercise include the following: Metric Scale, which is of the physician’s type. It has a movable rod in the range of 75 cm to 195 cm with an incremental scale of 1 cm. It is used to measure the stature; the eye standing, the shoulder standing, and elbow standing height. The metric scale is also equipped with a weighing balance of up to 160 kg capacity an incremental unit of 100 gram (0.1 kg). The weight measurements are recorded to the nearest 0.5 kg. The Metric Scale is shown in figure (2).Chest Depth Caliber, which is of the physician’s type. It has a movable rod in the range of 1cm to 60 cm with an incremental scale of 1cm. It is used to measure the chest depth, chest breadth, waist depth, waist breadth, head length, head breadth and neck breadth. The Chest Depth Caliber is shown in figure (3).Breadth Scale, which is of the physician’s type. It has a movable rod in the range of 1 to 100 cm with an incremental scale of 1 cm. It is used to measure the shoulder breadth, hip breadth, upper limb breadth, forward grip reach, elbow fingertip length, shoulder elbow length, thigh thickness, buttock-knee length, foot length, foot breadth, hand length and hand breadth. The Breadth Scale is shown in figure (4).Fat Caliper (Skin Fold Caliper), which is adjustable from 1 to 60 mm with increment of 1 mm. It is used to measure fatness. The Fat Caliper is shown in figure (5).654050584835000312483556197506667501875155Figure SEQ Figure \* ARABIC 2the Metric Scale0Figure SEQ Figure \* ARABIC 2the Metric Scale34569401814830Figure SEQ Figure \* ARABIC 3 Chest depth CaliperFigure SEQ Figure \* ARABIC 3 Chest depth Caliper360045-285750806452190750Figure SEQ Figure \* ARABIC 4 Skinfold caliperFigure SEQ Figure \* ARABIC 4 Skinfold caliper6350-2546351492252200275Figure SEQ Figure \* ARABIC 5 flexible tape measuresFigure SEQ Figure \* ARABIC 5 flexible tape measurescentercenter00140335Figure SEQ Figure \* ARABIC 6 Shoulder caliperFigure SEQ Figure \* ARABIC 6 Shoulder caliperResultsThis experiment measures different anthropometric parameters for all the group’s students, shown in table 1.Table SEQ Table \* ARABIC 1 Sample Data of Group's studentsNo.Variables NameStudent #1Student #2Student #33Age22214Ethnic OriginArabAsian5Father’s OccupationManagerTeacher6Family Size897Weight525870.58Height1521571709Eye Height Standing142146157.510Shoulder Height standing12812814111Elbow Height Standing9496106.512Waist Height Standing989310813Standing Vertical Grip Reach18218620914Height Setting77778715Eye Height Sitting68657416Shoulder Height Sitting51495417Elbow Height Sitting15182118Sitting Vertical Grip Reach10311311919Over knee Height From Floor51515520Under knee Height From Floor43424721Chest Depth202425.522Chest Breadth223626.523Waist Depth18222624Waist Breadth25323025Head Length181918.526Head Breadth15211527Neck Breadth891028Shoulder Breadth38.2443829Hip Breadth36353830Upper Limb Length7065.576.531Forward Grip Reach69677532Elbow Finger Tip Length42403933Shoulder Elbow Length37.2323734Tight Thickness15161835Buttock Knee Length51555636Buttock to Hollow of Knee Length43494837Foot Length21222438Foot Breadth7.699.539Hand Length18171840Hand Breadth8.591041Fat Thickness30202742Chest circumference81889843Waist circumference68.77790.5CalculationsIn this experiment, each student in each group will take one variable to measure and compare the sample result with population’s result. Population data is shown in table 2.Table SEQ Table \* ARABIC 2 The Population data of the variables that will be measureVariables:No.17: Elbow height setting18: sitting vertical grip reach19: Over knee Height From Floor122.511650221.511749.5318113514151035152111350616115487231145082111650920103541026117551120109521223111511322102.5521420110501520107511624112521725.5119541832123561930.5114.544203213958212311454222512155232010751242111955251611556262910250272210251282011152293112353302316352312912051322010952332010751342210251Table SEQ Table \* ARABIC 3 The Categories that each student will compare withVariableStudent #1Student #2Student #317- Elbow height settingCategory = 1518 - Sitting Vertical Grip ReachCategory =11319 - Over knee Height From FloorCategory = 55Student #1 Student number 1 will takes variable number 17 which is Elbow height setting and performs a hypothesis testing using Minitab, and calculating the goodness of fit using Chi-Square test.First: The hypothesis is:H0: The Population data are normally distributed for variable no. 17H1: The Population data are not normally distributed for variable no. 17Second: Entering the population data in Minitab and perform the Chi-Square goodness of fit test.Third: The result is:60960032575500060960019050Figure SEQ Figure \* ARABIC 7 The Expected and Observed values of the population of Variable 17Figure SEQ Figure \* ARABIC 7 The Expected and Observed values of the population of Variable 17Calculating result: Chi-Square = 26, P-Value = 0.054Tabulated result: Chi-Square = 26.296, α = 0.05Concluding result: Since, Chi-Square = 26 < 26.296 and, P-Value = 0.054 > α = 0.05, Do not reject H0 and conclude that the data is normally distributed for variable 17 which is the Elbow height sitting. Comparison: Student #1 has a Category = 15 which has a value = 1.Since 1 is near the expected value = 2 that is shown in figure 7, then, the category that student #1 has, does not cause significant difference.Calculation of the Percentiles: For the normal distribution the any percentile can be calculatedusing the following formula:Xp= X + Zp * SwhereXp is the percentile valueX is the average value of the sample dataZp is the value of Z from the standard normal distribution table that corresponding to the desired percentileS is the standard deviation value of the sample dataThe Z values of the standard normal distribution corresponding to the commonly used percentiles are shown on table 4 below:Table SEQ Table \* ARABIC 4 The Z valuesPercentilePZp1st0.01-2.332.5th0.025-1.965th0.05-1.6410th0.1-1.2817th0.17-0.95550th0.50.0083rd0.830.95590th0.91.2895th0.951.6497.5th0.9751.9699th0.992.33The 5th percentile can be calculated as follows:X0.05= X + Z0.05 * SX0.05 = 16 cmThe 50th percentile= X0.5 = 22 cmThe 95th percentile=X0.95 = 31.35 cmWe can conclude that 95% from the population has elbow height while setting of 16cm, 50% has 22cm and 5% has 31.35cm.Student #2 Student number 2 will takes variable number 18 which is sitting vertical grip reach and performs a hypothesis testing using Minitab, and calculating the goodness of fit using Chi-Square test.First: The hypothesis is:H0: The Population data are normally distributed for variable no. 18H1: The Population data are not normally distributed for variable no. 18Second: Entering the population data in Minitab and perform the Chi-Square goodness of fit test.Third: The result is:-406973015590004368804119245581025307975Figure SEQ Figure \* ARABIC 8 The Expected and Observed values of the population of Variable 18Figure SEQ Figure \* ARABIC 8 The Expected and Observed values of the population of Variable 18Calculating result: Chi-Square = 4.82353, P-Value = 1.00Tabulated result: Chi-Square = 30.144, α = 0.05Concluding result: Since, Chi-Square = 4.82353 < 30.144 and, P-Value = 1 > α = 0.05, Do not reject H0 and conclude that the data is normally distributed for variable 18 which is sitting vertical grip reach. Comparison: Student #2 has a Category = 113 which has a value = 2.Since 2 is near the expected value = 1.7 that is shown in figure 8, then, the category that student #2 has, does not cause significant difference.Calculation of the Percentiles: The 5th percentile can be calculated as follows:X0.05= X + Z0.05 * SX0.05 = 102 cmThe 50th percentile= X0.5 = 113.5 cmThe 95th percentile= X0.95 = 128.6 cmWe can conclude that 95% from the population has elbow height while setting of 102cm, 50% has 113.5cm and 5% has 128.6cm.Student #3 Student number 3 will takes variable number 19 which is over knee Height from Floor and performs a hypothesis testing using Minitab, and calculating the goodness of fit using Chi-Square test.First: The hypothesis is:H0: The Population data are normally distributed for variable no. 19H1: The Population data are not normally distributed for variable no. 19Second: Entering the population data in Minitab and perform the Chi-Square goodness of fit test.Third: The result is:562997-472440565843227198Figure SEQ Figure \* ARABIC 9 The Expected and Observed values of the population of Variable 19Figure SEQ Figure \* ARABIC 9 The Expected and Observed values of the population of Variable 19Calculating result: Chi-Square = 24.2353, P-Value = 0.007Tabulated result: Chi-Square = 18.307, α = 0.05Concluding result: Since, Chi-Square = 24.2353 >18.307and, P-Value = 0.007 < α = 0.05, Reject H0 and conclude that the data is not normally distributed for variable 19 which is knee Height from Floor. Comparison: Student #3 has a Category = 55 which has a value = 3.Since 3 is near the expected value = 3.09091 that is shown in figure 9, then the category that student #3 has, does not cause significant difference.Calculation of the Percentiles:The 5th percentile can be calculated as follows:X0.05= X + Z0.05 * SX0.05 = 48.975 cmThe 50th percentile= X0.5 = 51 cmThe 95th percentile= X0.95 = 56 cmWe can conclude that 95% from the population has elbow height while setting of 48.975cm, 50% has 51cm and 5% has 56cm.ConclusionReferences BIBLIOGRAPHY [1] "umtri," [Online]. Available: . [Accessed 27 2 2016]. ................
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