Optimization of Physical Working Environment Setting to Improve Productivity and Minimize Error by Taguchi and VIKOR Methods

Transcription

1 IOP Conference Seres: Materals Scence and Engneerng PAPER OPEN ACCESS Optmzaton of Physcal Workng Envronment Settng to Improve Productvty and Mnmze Error by Taguch and VIKOR Methods To cte ths artcle: Fety Ilma Rahmllah 2016 IOP Conf. Ser.: Mater. Sc. Eng Vew the artcle onlne for updates and enhancements. Related content - Usng Qualty Management Methods n Knowledge-Based Organzatons. An Approach to the Applcaton of the Taguch Method to the Process of Pressng Tappets nto Anchors M A îu, A B Pop and îu - Modellng and mult objectve optmzaton of laser peenng process usng Taguch utlty concept G Ranjth Kumar and G Rajyalakshm - Study on surface fnsh of AISI 2080 steel based on the Taguch method S Yalcnkaya and Y ahn Ths content was downloaded from IP address on 26/04/2018 at 01:01

2 Optmzaton of Physcal Workng Envronment Settng to Improve Productvty and Mnmze Error by Taguch and VIKOR Methods Fety Ilma Rahmllah Department of Industral Engneerng Unverstas Islam Indonesa Yogyakarta, Indonesa E-mal: Abstract. The workng envronment s one factor that has contrbuton to the worker s performance, especally for contnuous and monotonous works. L 9 Taguch desgn experment for nner array s used to desgn the experment whch was carred out n laboratory whereas L 4 s for outer array. Four control varables wth three levels of each are used to get the optmal combnaton of workng envronment settng. Four responses are also measured to know the effect of four control factors. Results shown that by usng ANOVA, the effect of llumnaton, temperature, and nstrumental musc to the number of ouput, number of error, and ratng perceved dscomfort s sgnfcant wth the total varance explaned of 54,67%, 60,67%, and 75,22% respectvely. By usng VIKOR method, t yelds the optmal combnaton of experment 66 wth the settng condton of A 3-B 2-C 1-D 3. The llumnaton s lux, temperature s C, fast category of nstrumental musc, and db for ntensty of the musc beng played. Keywords: Workng envronment, llumnaton, temperature, musc, ANOVA, Taguch, VIKOR 1. Introducton Physcal workng envronment s one factor affectng productvty [1][2]. Physcal workng envronment factors such as colorng n clean and clear workng envronment, good lghtng and ventlaton, musc played, nose, and temperature are necessary to be well desgned suts wth the workers characterstcs so that humans can perform work actvtes effectvely and effcently. But, f the workers are not comfort wth ther workng envronment, ther performance wll not be maxmum. Even, t can make them faster to get bored and fatgue, moreover for contnuous and monotonous works [3]. Actvtes whch are categorzed as monotonous job are sewng, typewrtng, proofreadng, offce task, and vsual nspecton tasks n manufacturng settngs. A task s monotonous when ts stmulants do not change or the changes are predctable or there s a hgh type of repetton [4]. Headache and occurrence of accdents lke needle-percng because of the vsual stran are caused by nsuffcent lght at the workng area [5]. Content from ths work may be used under the terms of the Creatve Commons Attrbuton 3.0 lcence. Any further dstrbuton of ths work must mantan attrbuton to the author(s) and the ttle of the work, journal ctaton and DOI. Publshed under lcence by Ltd 1

3 Reference [5] stated that 42.5% of respondents n textles and clothng sector felt of eye stran because of poor workng condton. Ths data actually has smlartes wth the condton of workers n garment ndustry [6]. Scholar [2] had been done a research related wth physcal workng envronment and ts nfluence to the cvl servants n Malaysa whle scholar [1] dd the research to the workers n selected ol and gas ndustry n Ngera. Questonnare s used to collect the data and the result showed that there was sgnfcant relatonshp between physcal envronments (comfort level, temperature) wth cvl servants productvty [2]. Reference [7] found that human error s sgnfcantly affected by four major factors explored, whch are stress, repetton, fatgue, and work envronment by approxmately 48.8%. A frendly physcal workng envronment can be created through applcaton of background musc. Reference [8] has proved t by dong ths research to the workers n garment manufacturng company n Sr Lanka. Accordng to [9], the musc should be only nstrument; because f there was a lyrcs, people wll concentrate to the lyrcs, not to the musc; and t could be annoyng. Even, the study [9] contrbutes to the feld of utlzng musc to nfluence human performance n the workplace. The Taguch method s a powerful method of solvng qualty problems n varous felds of engneerng.the Taguch method can be utlzed to fnd the sequence of domnant factors that contrbuted to the productvty of the operator at the specfed producton work staton. Even, t can sgnfcantly reduce the tme requred for expermental nvestgaton, as t s effectve n nvestgatng the effects of multple factors on performance as well as studyng the nfluence of ndvdual factors to determne whch factor has more nfluence, and whch less. Research [10] was done n automotve components assembly factory, and examned envronmental factors such as llumnance, humdty and WBGT whle the response factor s producton rate. The study reveals that the domnant factor that contrbuted to the productvty was humdty, followed by llumnance and WBGT. The recent study ams at knowng the relatonshp among some factors such as temperature, llumnaton, beat of nstrument, and ntensty of musc by usng Analyss of Varance (ANOVA). The second objectve s fndng the optmum comfort level of sewng workng envronment settng by usng VIKOR to mprove productvty and mnmze error by consderng four responses whch are number of output, average of eye blnk, number of error, and ratng perceved dscomfort (RPD). 2. Research Method The experments were carred out n Clmate Room of Work Desgn Analyss and Ergonomc Laboratory Unverstas Islam Indonesa. The subject was asked to sttch beads n the vel durng one hour experment. They have to pass the tranng untl reach certan amount of producton so that the sklled and unsklled factor can be mnmzed to prevent bas. Eye blnk and ratng perceved dscomfort are used to know when the fatgue happens. Those two knds of measurements are used to mutually complete each other whereas the number of error s to ndcate the accuracy level of the worker s job. Before dong experment, subject was asked about ther healthy condton and RPD. That s because the unhealthy condton can affect the expermental result. RPD s used to know whether the subject was n fresh eye condton or sleepless. The maxmum score s 0.5, f the subject has more than 0.5, so that they asked to come at another day. Each of experments was done for one hour. Durng the experment, subject are not allowed to do other actvtes or talkng wth other people because t could affect the experment result Data Requrement The data requred n ths research are: 1. Number of output. It can be calculated from how many unt of beads that can be sttched n the vel durng one hour experment. Ths relates to the productvty of workers. 2. Average of eye blnk. It s measured by drect observaton and then make an average of the amount of eye blnk for every 5 mnutes of 0 5 th mnute, 5 th -10 th mnute, 10 th -15 th mnute, 45 th - 50 th mnute, 50 th -55 th mnute, and 55 th -60 th mnute. Blnkng s a common facal moton and 2

4 reflectng a person s emotonal or cogntve state [11]. There are many factors that can affect blnk rate such as loud noses, flashng lghts, tasks, and envronment (room temperature and humdty) [12]. 3. Number of error. It s calculated from the amount of error n sttchng beads such as sewng result s not straght, the thread s not locked, and the beads sewed s unsymmetrc. 4. Ratng Perceved Dscomfort (RPD) s based on Borg s General Scale (Table 3). The subject s asked to menton the eye fatgue scale that s experenced after one hour experment. 5. Workng area temperature. Frst type ( C) s a cold comfortable workng area where some jobs are good when t s done n ths temperature; second type ( C)] s the comfort zone for Indonesan clmate s C [13][14], and thrd ( C) s the real condton. 6. Illumnaton. Frst type s lux, second type s lux, and thrd s lux. Those all of ntensty actually already fulflled the requrement of llumnaton for sewng actvty [14]. It s measured by usng Luxmeter. 7. Beat of nstrumental. Frst type s fast, second type s slow, and the thrd s mddle. 8. Intensty of nstrumental. It varates from db, db, and db. The good effect of background musc can reduce wrong fnger touch n typng task [9]. Table 1. Control factors and types No. Control Factors Illumnaton lux lux lux 2. Temperature C C C 3. Beat of nstrument Fast Slow Mddle 4. Intensty of musc db db 70-80B Table 2. Nose factor and type No. Nose factor Age years old years old Table 3. Borg s General Scale [14] Score Type of Fatgue 0 Nothng at all 0.5 Extremely weak (just notceable) 1 Very weak 2 Moderate 3 Somewhat strong 4 Strong Very strong 8 Strong 9 10 Extremely strong (almost maxmal) Table 4. Responses No Response 1 Number of Output (Larger the Better) 2 Average of Eye Blnk (Smaller the Better) 3 Number of Error (Smaller the Better) 4 RPD (Smaller the Better) The data s collected by dong some experments based on L9 desgn experment from Taguch as shown n Table 5 wth twce replcaton. Then, SNR values for all responses are calculated. If the 3

5 combnaton experment for all responses s dfferent, then VIKOR s used to fnd the result. The next step s dong confrmaton experment to valdate the result obtaned. Tabel 5. Expermental Desgn usng L9 Orthogonal Array L4 OA (Outer Array) E 1 2 L9 IA (Inner Array) Experment Data A B C D Y1 Y2 Column Number Run Technque for Analzng Data Sgnal Nose Rato (SNR) The number of output wll use Larger the Better (LTB) whereas average of eye blnk, number of error, and RPD use Smaller the Better (STB). The equaton to calculate SNR s below. n SNRLTB Log 1 1 (1) 2 n y n SNR STB 10 Log 1 n n n y 2 where: n = number of tests n the experment (tral) y 1 = response value for each replcaton Multple Lnear Regresson The common model s: y 0 = b 0 + b 1x 1 + b 2x b kx k + e (3) VIKOR VIKOR requres performance ratng of each alternatve on each crteron A C j wrote normalzed calculated by: r x m 1 x 2 where : = 1, 2,..., m and j = 1, 2,..., n Postve deal soluton A + and the negatve deal soluton A - ratng can be determned based on normalzed weghts (y ) as follows: (2) (4) 4

6 y = w r (5) where: = 1, 2,..., m and j = 1, 2,..., n. A + = (y 1 +, y 2 +,..., y n + ) A - = (y 1 -, y 2 -,..., y n - ) where y j y j max mn mn max y ; y ; y ; y ; f js proft attrbute f js cost attrbute f js proft attrbute f js cost attrbute The next step s to determne the utlty of measurement (S ) and the measurement of regret (R ). S n y j y j 1 y y j y j y (8) j R max (9) y j y j Then calculate the ndex VIKOR, whch s: S S R R Q v 1 v S S R R The smallest the value of Q (VIKOR ndex) shows that best alternatve A then be selected Confrmaton Experment Ths step ams to valdate the concluson resulted by usng Wlcoxon Sgned Test. It s used to test the dfference of nonparametrc repeated measured data. SPSS software s used to do ths test Analyss of Varance It s used to dentfy the contrbuton of each factor to all responses. The table s as follow: (6) (7) (10) Table 6. Analyss of Varance Source Sq V Mq F rato Sq ρ% Factor A S A v A M A = S A / v A S A-v A.v E 100% Factor n S n v n M n = S n /v n S n-v n.v E 100% Error S E v E M E = S E / v E 1 Total S T N - 3. Results And Dscusson The objectve of the experment s to optmze the envronmental parameters (temperature, llumnaton, beat of nstrument, and ntensty of musc) n order to obtan a better productvty and mnmum error and therefore the optmum characterstcs should be quantfed. The second one s to 5

7 know the relatonshp among four responses and control factors. All the expermental data are already tested ther normalty and categorzed as normal. 4. Effect of Factors to Responses Table 7 and 8 show the optmal combnaton for each of responses. A 3-B 2-C 4-D 1 s the optmal combnaton for number of output whereas the optmal combnaton for average of eye blnk conssts of A 3-B 1-C 4-D 2. Based on those table, t can be seen that the rank s dfferent each other. Table 7. SNR effect to number of output and average of eye blnk. Output Eye blnk A B C D A B C D Type Type Type Delta Rank Table 8. SNR effect to number of error and RPD Output Eye blnk A B C D A B C D Type Type Type Delta Rank Multple Lnear Regresson Ths step s used to predct the correlaton and t follows equaton (3). The results are: Y 11 = X X X X 4 (R 2 =0.892) Y 12 = X X 2 3X X 4 (R 2 =0.895) Y 13 = X X X X 4 (R 2 =0.611) Y 14 = X X X X 4 (R 2 =0.805) Meanwhle the multple lnear regresson for number of error are: Y 31 = X X X X 4 (R 2 =0.851) Y 32 = X X X X 4 (R 2 =0.639) Y 33 = X 1 + 2X X X 4 (R 2 =0.705) Y 34 = X X X X 4 (R 2 =0.805) By usng the same way n SPSS, the multple lnear regresson for RPD are: Y 41 = X X 2 0.5X X 4 (R 2 =0.810) Y 42 = X X X X 4 (R 2 =0.820) 6

8 Y 43 = 2 0.5X X X X 4 (R 2 =0.837) Y 44 = X X X X 4 (R 2 =0.840) The R 2 value of eye blnk response s not reach 0.8, so that eye blnk response s not used Analyss of Varance (ANOVA) The purpose of ANOVA s to nvestgate whch of the factors sgnfcantly affect the workers productvty by usng F-test, statstcally. The larger the value of F, the greater the effect on the performance characterstcs. When F>4, t means that the change of operatng factors has a sgnfcant effect on the qualty characterstcs. Table 9. Analyss of Varance for Number of Output Factors Sq V Mq F Sq P (%) Illumnaton Temperature Beat of Instrumental Intensty of Musc Error ST Table 10. Analyss of Varance for Number of Error Factors Sq V Mq F Sq P (%) Illumnaton Temperature Beat of Instrumental Intensty of Musc Error ST Table 11. Analyss of Varance for Ratng Perceved Dscomfort (RPD) Factors Sq V Mq F Sq P (%) Illumnaton Temperature Beat of Instrumental Intensty of Musc Error ST It can be seen on Table 9 that only temperature and beat of nstrumental musc whch statstcally have sgnfcant nfluence toward number of output (F>4). From ths result, t s known that there s other factor that also gve nfluence snce the error s 45.33%. Whle llumnaton and ntensty of musc beng played nfluence the number of error sgnfcantly as shown n Table 10 (p 7

9 value s 29.88% and 22.36%). Table 11 presents that all factors have sgnfcant effect toward ratng perceved dscomfort of the subjects. The accumulaton of contrbuton of those four factors reach 75.23%, t can be concluded that those four factors have to be really consdered n order to make a good workng envronment. Eventhough Ratng Perceved Dscomfort s a subjectve measurement, but sometme t can really represent the condton of someone because they felt t by therself. But of course, the other measurement should also be used to complete n order to get the real effect. Based on ANOVA test, the effect of total factors whch are llumnaton, temperature, beat of nstrument and ntensty of musc to the number of output, number of error, and RPD are 54.67%, 60.67%, and 75.22%, respectvely. It means that those factors are necessary to be consdered to fnd the best workng envronment settng VIKOR Tabel 7 and 8 show the dfferent optmal condton for all responses so that t s necessary to decde the optmal combnaton experment by usng VIKOR method. To calculate the score of SNR of each response, equaton (1) s used to calculate response number of output whereas equaton (2) s for response number of error and Ratng Perceved Dscomfort. The example s shown below. SNR 11=-10 Log [1/4*(0.0005)] = 3.88 SNR 11=-10 Log [1/4*(507)] = SNR 11=-10 Log [1/4*(74.25)] = Equaton (4) s to determne the normalzed decson score. = = (Number of output) = = (Number of error) = = (RPD) (Number of output) (Number of error) (RPD) Whle equaton (5) s to defne the postve and negatve deal soluton by consderng the weght for each response whch s equal to y 11 = x 0.33 = y 11 = x 0.33 = y 11 = x 0.33 = (Number of output) (Number of error) (RPD) Then, the results wll be summed at the smlar poston: y 11 = y 11 (number of output) + y 11 (number of error) + y 11 (RPD) = (-0.048) + (-0.054) = The postve deal soluton (A + ) s calculated based on equaton (6) whereas equaton (7) s to count the negatve deal soluton. y 1+ = max (-0.064; ; ; ) = y 1 - = max (-0.064; ; ; ) = The next step s determnng utlty measurement (S ) measurement (R ) by usng equaton (9). = ( ( 0.064)) + + ( ( 0.046)) ( 0.029) ( 0.064)) = = = (. (. )) (. (. )) (. (. )) (. (. )) =1 = 1 = by usng equaton (8) and regret 8

10 VIKOR score s the closest value of each responses to the deal soluton and t can be quantfed based on equaton (10). = + (1 ) = 0.5 (.. ) (.. ) ( (. )) ( (. )) = Based on VIKOR calculaton, t can be concluded that the optmal combnaton s experment 66 (A 3-B 2-C 1-D 3) whch s llumnaton of lux, temperature of C, fast nstrumental musc, and db for ntensty of the nstrumental musc beng played. Ths experment produced the number of output, number of error, and RPD score of , 3.75, and 3 respectvely. Table 12 shows the comparson of the predcton result and confrmaton experment. Wlcoxon test whch s used to test the experment confrmaton shown value of means that there s no sgnfcant dfference snce t s more than Table 12. Comparson of result and confrmaton experment Output Error RPD Y 1 Y 2 Y 3 Y 4 Y 1 Y 2 Y 3 Y 4 Y 1 Y 2 Y 3 Y 4 Predcton Confrmaton For the llumnaton, t s already relevant snce the hgher the ntensty s better for hand sewng whch s need hgh accuracy. A good llumnaton wll make the worker easly to see the object or the tools used n dong the job and t s n such a way that the vsblty of the needleponts wll be optmum [14]. Based on the observaton whle experment conducted, the amount of llumnaton ntensty s not appearng glare. For the temperature, t suts wth some researches [13][14], n whch C s categorzed as comfortable workng area, but the duraton should be consdered. If t s for a long duraton of work, some negatve effect wll start to appear such as psychcal or physologcal problems [14]. The result of ths research fnd that the best s fast beat of nstrumental musc for sewng actvty n whch t s not a complex task. If the beat s low, t can make workers to easly get bored or sleepy. However, t was not nlne wth reference [15] snce t sad that n the workplace, faster tempos of background musc may cause declnes n worker output, especally f the employee s engaged n a complex task. Reference [15] also stated that playng background musc n the classroom s benefcal and teachers need to be cognzant of the tempo of the background musc. For the ntensty of nstrumental musc, that amount s permtted. It s stll safe, not becomng a nose factor snce the louder the sound, t can dsturb the worker. Lstenng to musc can make a postve mood and enhanced percepton on desgn whle workng [16]. Bascally, the nfluence of musc on ths performance s dffcult to be measured because many factors are nvolved such as preferences what knd of musc whch they lke. CONCLUSION Ths study was done to emprcally prove the percepton of the effect of work envronment factors towards productvty and error. Based on ANOVA test, the effect of total factors whch are llumnaton, temperature, and nstrumental musc to the number of output, number of error, and RPD s 54.67%, 60.67%, and 75.22%, respectvely. From all of processes that have been done n ths research, those can be concluded that the optmal combnaton of workng envronment settng for sewng actvty as one of monotonous work s experment 66, wth the settng condton of A 3-B 2-C 1- D 3 or llumnaton of lux, temperature of C, beat of nstrumental musc s fast, and db for ntensty of the nstrumental musc beng played. The fndngs wll also be useful to engneers n the desgn of workng envronment system for other monotonous work to mprove the comfort of the work staton area and control productvty of workers. 9

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