This paper describes a case study conducted at a manufacturing company aimed at improving productivity using line balancing. Two alternatives were generated using different assignment rules. However selection of the most suitable alternatives cannot be made based on line balancing alone as they appear similar based on line balance loss. Thus the robustness of the alternatives were tested and evaluated using a 16 factorial ANOVA. Selection of the most suitable solution is then made based on these results

Lim, Chuan Pei

Md. Tap, Masine

English

Universiti Teknologi Malaysia Institutional Repository

Jumal MekanikalDisember 2002, Bil. 14, 48 - 62IMPROVING PRODUCTIVITY THROUGH LINEBALANCING - A CASE STUDYLim Chuan PeiMasine Md. TapFaculty of Mechanical Engineering,Universiti Teknologi Malaysia,81310 UTM SkudaiABSTRACTThis paper describes a case study conducted at a manufacturing company aimed at improvingproductivity using line balancing. Two altematives were generated using different assignmentrules. However selection of the most suitable altematives cannot be made based on linebalancing alone as they appear similar based on line balance loss. Thus the robustness of thealtematives were tested and evaluated using a 16 factorial ANOVA. Selection of the mostsuitable solution is then made based on these results.Keyword: Productivity improvement, Line balancing, Simulation.1.0 INTRODUCTIONMany researchers have reported various productivity techniques and performancemeasures designed to monitor and improve system performance in anorganization [1,2,3,4]. Some deal with specific problems such as inventory,scrap and set-up time reduction, with the aim of increasing manufacturingproductivity. One of these techniques is line balancing.Line balancing aims to match the output rate to the production plan [5]. Thiswill assist management in ensuring on-time delivery and prevents buildup ofunwanted inventory. Johnson [6] expresses the problem of line balancing as 'aset of nondivisible tasks to be performed, Each task has a known deterministicperformance time. A partial ordering of tasks by precedence constraints isspecified. The problem is to assign these tasks to assembly stations, so that thenecessary number of station is minimized.' The steps to line balancing has beendetailed out by Hoffman [7].This paper reports an effort to improve the productivity of a manufacturingcompany by improving the line balancing of one of its assembly lines. Twoalternatives were generated and evaluated. Both alternatives showed markedimprovements as compared to the existing line. However the difference betweenboth alternatives in terms of line balance loss is too small to enable a clear choicebetween the two to be made. The robustness of each alternative is checked using48Jurnal Mekanikal, Disember 2002simulation and 16-factorial ANOVA. Based on these results the appropriatealtemative is recommended.2.0 PROBLEM DEFINITIONCurrently, the SL-D assembly line faces the problem of fulfilling the targetedproduction plan. To fulfill the production plan, overtime work is conducted.This increases the production costs and reduces company profit.Figure 1 shows the comparison between the actual output and the productiontarget for the month of July. It is representative of other months. This output isbased on normal working period of one shift per day without overtime. The lineacross the graph is the targeted output of the product which is 850 units per day.This production capacity is calculated by the production planner based on theavailable machines and human resources. It shows that only a few of the dailyactual outputs reached the targeted production capacity. Although 20% of thetime output surpassed the targeted production, it cannot compensate for the other80%. Observations and investigations show that the main cause for this is due tounbalanced assembly line. Figure 2 shows graphically the line balance loss(LBL) of each work station. It also shows that some workstations tend to be thecause for bottlenecks as these stations handled more workload as compared toother stations, for example workstations 3, 5, 14 and 39. In contrast,workstations 35 and 38 are very often idle.The LBL percentage is presented to identify the seriousness of the problem.LBL is calculated as follows:Line Balance Loss Percentage:nT - Lt.%LBL = max I XlOO%nTmax= (39X35.84)-519.46 XlOO%(39X35.84)=62.84%where;n =number of workstationsTIIUlX =value of the highest cycle timeIt t, =Total cycle time49Jurnal Mekanikal, Disember2002The result shows that this assembly line is more than 60% unbalanced. Thus,some effective action must be taken to balance the assembly line, as well as toincrease the productivity of the assembly line.To facilitate line balancing, other information related to the line such asprecedence relationship of the work tasks or workstation was also collected.Precedence requirements are physical restrictions on the order in whichoperations are performed on the assembly line. Figure 3 illustrates the precedencediagram for the assembly line SL-D. It portrays the elemental tasks to beperformed and sequence requirements of the assembly processes.3.0 PROPOSED SOLUTIONThe assembly process involves a set of workstations, each carrying out a specifictask or tasks in a restricted sequence. It is important that tasks be allocated toeach workstation as evenly as possible to avoid bottlenecks and excessive idletime. Line balancing involves assigning and balancing tasks betweenworkstations of the assembly line in order to minimise balance delay, labourforce and ultimately minimising the total production cost. Two alternativesolutions are proposed. Ranked positional weight was used to generateAlternative 1. Whereas, Alternative 2 is generated by modifying Alternative 1based on the concept of eliminating, combining, simplifying the assemblyprocess without any additional machine and manpower in the hope that furtherimprovement may be achieved.The cycle time of each workstation is kept to within 29 seconds. This value iscalculated based on the required production rate and the cycle time.3.1 Alternative 1The alternative solution is generated based on the 'ranked positional weight' rulein selecting tasks for workstations. Specifically, this rule states that tasks thatmeet precedence criteria are assigned according to their positional weights, whichare times for a given task plus the task times of all those that follow. The taskwith the highest positional weight would be assigned to the first station.Recommended changes to the assignment of task to each operator in the line are:• Transfer work task of operator 3 to operator 2 (back board sub-assembly).Thus saving one manpower in the line.• Combined work task of operators 4, 5 and 6 in baffle board sub-assembly tomeet total process time of 25 seconds. In this case, using multiskilled operatorto operate the workstation as a team rather than as independent workers.• Transfer work task of operator 12 to operator 11 (triangle wood attachment)and adjacent operator 10 to assist operator 11. Thus, saving one manpower inthe line.• Combined work tasks of operator 14 (sanding and touching up) with operator13 to eliminate the slack time between workstations 7 and 8.• Transfer work task of operator 25 (lens fixing) to operator 24.50Jumal Mekanikal, Disember 2002• Combine work task of operator 31 (duct fixing) and operator 30, and usingmultiskilled operator to operate the workstation as a team rather than asindependent workers.• Transfer work task of operator 44 (polyfoam placement) to operator 43. Thus,saving one manpower in the line.3.2 Alternative 2The second alternative solution is generated by modifying the Alternative 1.Modification is made based on the concept of eliminating, combining andsimplifying the assembly process without any additional machine and manpower.Changes to the assignment of work task to each operator in the line are:• Transfer work task of quality operator QA2 (electronic component checking)to QAl (terminal cord plug in), to eliminate QA2 in the line.• Transfer work task of operator 24 (wood ADH) to operator 23 (layerprotection).• Transfer work task of operator 26 (lens screwing) to operator 25 (lens fixing),and operator 25 would take over the entire combined work tasks.• Eliminate operator 29 (screwing), and operator 28 (front panel fixing) wouldtake over the combined work tasks. Improve work method of operators 27 and28 (station 13) to deal with cycle time in 29 seconds by reducing the task time.• Combine workstation 28 (QC appearance checking) and workstation 27 (setcleaning and matching). In this case, using two multiskilled operators tooperate the workstation as a team rather than as independent workers. Thus,saving two manpower in the line.Tables 1 and 2 show the workstations and process time of each station in SL-Dassembly line for Alternatives 1 and 2 respectively.In formulating Alternatives 1 and 2, these assumptions have been made;i. The process cycle time for every work task is based on existing records.ii. Mean time between failure and mean time to repair is modelled using theexponential distribution [8].iii. For the combined work tasks, the new process cycle time is the average oftotal time of the work tasks.iv. For the task that is assigned to another operator, the cycle time is based onrecords of the existing system.v. The machine speed or production rate is constant.vi. The skill and experience level of all operators are considered to be the same.Both alternatives need to be evaluated to quantify the amount of improvementpossible over the existing situation and also to determine the optimum alternative.51Jumal Mekanikal, Disember 20024.0 EVALUATION OF PROPOSED SOLUTIONSFigures 4 and 5 show the bar charts for process time and idle time forAlternatives I and 2 respectively based on Tables I and 2 respectively. Table 3summarises the differences in the results of various parameters of the existingand alternative systems. These parameters include line balance loss, number ofoperator, number of station, total lead-time of line and total distance of line. Itshows that Alternatives 1 and 2 have the potential of producing significantimprovement over the existing situation.However comparison between Alternatives I and 2 shows that overallAlternative 2 is slightly better. Alternative 2 requires less operator as comparedto Alternative I while all other parameters are almost equal. To further verifythat Alternative 2 is indeed the best alternative the robustness of both alternativesis tested.Simulations have been carried out to test the robustness of these alternatives.Witness software was used for this purpose. The model of each alternative issubjected to extreme levels of station downtime, processing time and inventoryas shown in Table 4. This simulation uses a 2 x 2 x 2 x 2 (16) factorial ANOVAalong with pair-wise comparisons and family confidence intervals to study thefollowing;1. The effect of high and low levels of station coefficient of variation to theperformance of each line.n. The effect of high and low levels of station downtime to the performance ofeach line.iii. The effect of high and low levels of inventory in the system to theperformance of each line.Figures 6, 7 and 8 show the results of the simulation experimentations.Performance is measured based on the total output of each line. These resultsindicate that Alternative 2 is less affected by variability within the system thanAlternative 1. Alternative 2 appears to be able to achieve higher output levelunder both levels of system down time, coefficient of variation and extremelevels of inventory. Assembly lines less affected by variability within the systemshould enable management of factory to provide more reliable delivery ofproduct. Thus, Alternative 2 is selected as the best alternative as it not only usesthe least number of operators, it is also robust and less sensitive to changes.5.0 CONCLUSIONThe objective of this study is to improve the productivity of the assembly lineSL-D using line balancing. Two alternatives have been generated and evaluated.Evaluation based on line balancing loss shows that both alternatives52Jumal Mekanikal, Disember 2002outperformed the existing system. However, it was difficult to choose the bestalternative as they were almost equal to each other. Thus the robustness of eachalternative were simulated and evaluated using a 16-factorial ANOVA.Alternative 2 was found to be more robust than Alternative 1 and it is proposed tothe management of the company.This study also shows that in line balancing problem, line balancing loss maynot be the only criterion or measurement that may be used to determine theoptimum alternative especially in cases where alternatives are almost equal toeach other. The robustness of these solutions against the varyingly importantparameters should also be considered. A robust system will be able to performbetter in a real life environment where change and uncertainty are common.ACKNOWLEDGEMENTThe authors acknowledge the support given by Universiti Teknologi Malaysia inconducting this project.REFERENCES1. Baines, A., 1997, "Productivity measurement and reporting", Work Study46(5), PP. 160-161.2. Jonsson, P. and Lesshammar, M., 1999, "Evaluation and improvement ofmanufacturing performance measurement systems - the role of OEE',International Journal of Operations and Production Management 19(1), PP.55-78.3. Daniels, S., 1997, "Back to basics with productivity techniques", Work Study46(2), PP. 52-574. Craig, C.E. and Harris, R.C., 1973, "Total Productivity Measurement At TheFirm Level", Sloan Management Review, PP. 13-28.5. Krajewski, LJ. and Ritzman L.P., 1998, "Operations Management: Strategyand Analysis", Addison-Wesley.6. Johnson, R.V" 1983, "A Branch And Bound Algorithm For Assembly LineBalancing Problems With Formulation Irregularities", Management Science,PP. 1309-1324.7. Hoffmann, T.R., 1990, "Assembly Line Balancing: A Set Of ChallengingProblems", International Journal of Production Research, Vol. 28,PP. 1807-15.8. Mitra, A., 1993, "Fundamental of Quality Control and Improvement", NewYork, Macmillan.53Jumal Mekanikal, Disember 2002Table 1 Workstation balance based on Ranked Positional Weight (Alternative 1)Station Work Task Description Task Time RPW Station Process(sec) Time (sec)WSI 04,05,06 Baffle board assy. 35.84 480.85 29.00WS2 02 Back board assy. 22.06 467.07 22.06WS3 07 Back & baffle board assy. 18.51 445.04 18.51WS4 01&Ml Automation gluing 16.55 443.05 16.55WS5 08&09 SPK box assy. (1) 25.21 426.5 25.21WS6 010 SPK box assv. (ll) 16.52 401.29 22.11011 &M2 Trianzle wood attachment 5.59 384.77WS7 013 Acoustic snonae fixinz 13.25 379.18 29.00Sanding & touching 16.25 265.93WS8 015, M3 Drilling 9.59 349.68016 Speaker plug in 8.85 340.09 25.11017 Tweeter plug in 6.67 331.24WS9 018 Woofer placement 16.85 324.57 16.85WSlO 019,20,21,22 Screwing 26.53 307.72 26.53WSll QAl Terminal cord plug in 10.16 281.19QA2 Testing & checking 9.05 271.03 25.96023 Remove protect layer 6.75 261.98WS12 024 Apply wood ADH 5.08 255.23Lens fixing 5.56 250.15 22.28026 Lens screwing 11.64 244.59WS13 027 Front panel assy. 11.63 232.95 19.94028 Front panel fixing 8.31 221.32WS14 029 Front panel screwing 11.47 213.01030 Apply PCV ADH 12.52 201.54 29.00Duct fixing 6.23 189.02WS15 032 Duct screwing 15.54 182.79 27.45033 &034 Set cleaning & matching 11.91 167.25WS16 QA3 &QA4 QC appearance checking 14.76 155.34 23.76QAS QC polarity checking 9.00 140.58WS17 QA6 QC acoustic checking 12.79 131.58 26.81QA7 QC final checking 14.02 118.79WS18 035 Back label attachment 15.76 104.77 29.00036 Back label attachment 15.94 89.01WS19 037 & 038 PE bag packing 8.16 73.07039 Top polyfoam fixing 2.51 64.91 29.00040&041 Foot fixing 19.01 62.4WS20 041 &043 PE bag tapping 17.47 43.39 20.00Bottom polyfoam fixing 2.53 25.92WS21 045 &M4 Carton packing 23.39 23.39 23.3954Jumal Mekanikal, Disember 2002Table 2 Workstation balance for Alternative 2Station Work Task Description Task Time Improved Station(sec) Process Time (sec)WSI 04,05,06 Baffle board assy. 35.84 25.00WS2 02 Back board assy. 22.06 22.06WS3 07 Back & baffle board assy. 18.51 18.51WS4 01 &Ml Automation gluing 16.55 16.55WS5 08&09 SPK box assy. (I) 25.21 25.21WS6 010 SPK box assy. (II) 16.52 22.11011 &M2 Triangle wood attachment 5.59WS7 013 Acoustic sponge fixing 13.25 29.00014 Sanding & touching 16.25WS8 015, M3 Drilling 9.59016 Speaker plug in 8.85 25.11017 Tweeter plug in 6.67WS9 018 Woofer placement 16.85 16.85WSIO 019,20,21,22 Screwing 26.53 26.53WSll QAl Terminal cord plug in 10.16 19.21Testing & checking 9.05WS12 023 Remove protect layer 6.75Apply wood ADH 5.08 29.00025 Lens fixing 5.56Lens screwing 11.64WS13 027 Front panel assy. 11.63028 Front panel fixing 8.31 29.00Front panel screwing 11.47WS14 030 Apply PCV ADH 12.52Duct fixing 6.23 29.00032 Duct screwing 11.91WS15 033 &034 Set cleaning & matching 15.54 29.00QC appearance checking 14.76WS16 QA5 QC polarity checking 9.00 21.79QA6 QC acoustic checking 12.79WS17 QA7 QC final checking 14.02 29.00035 Back label attachment 15.76WS18 036 Back label attachment 15.94037 PE bag packing 8.16 29.00Top polyfoam fixing 2.51WS19 040&041 Foot fixing 19.01 19.01WS20 042 &043 PE bag tapping 17.47 20.00Bottom polyfoam fixing 2.53WS21 045 &M4 Carton packing 23.39 23.3955Jumal Mekanikal, Disember 2002Table 3 Comparison between existing line, Alternative 1 and Alternative 2System Existing Alternative 1 Alternative 21. Number of operators 53 47 412. Number of stations 39 21 213. Total lead time of line 519.46 485.91 484.05(second)4. Total distance of line 80.05 76.55 65.15(m)5. Line balance loss (%) 62.84 15.54 17.19Table 4 Simulation model parametersIndependent VariablesLine design (LD)Coefficient of variation (CV) of cycle timeDowntime (DT)Total inventory (INV)1 = Alternative 12 = Alternative 21 = 5 percent2 = 50 percent1 = 10 percent*2 = 30 percent* *1= 10 units2 =80 unitsLevelsNotes• The mean time between failures (MTBF) is distributed with a mean of 270, and themean time to repair (MTR) is log normally distributed with a mean of 30 and a standarddeviation of 9.•• The MTBF is exponentially distributed with a mean of 117, and the MTR is lognormally distributed with a mean of 50 and a standard deviation of 15.56Jurnal Mekanikal, Disember 2002Comparison between Actual Output and The Target Production Capacity2000:::- 1500'22-U 1000::J"00 500C-O~Do..date~ actual output --targeted capacity IFigure 1 The daily output of Model SP-MXGT 80 Series for July 200157lJII0040353025~e0~ 20.!!.IIIE;:151050Graph process time and Idle time for assembly line SL-D-., 1- 1- .,1] ~q;f-Df--D- .,i].'~i i§~i.,.kt'" I! ~,~ I~,'., ,;It ~f I11,, 1,.i,",",.T3 5 7 9 11 13 15 17 19 21 OP~ 25 27 29 31 33 35 37 39work stationOldie time• Process timeFigure 2 Line balance loss for assembly line SL - D?li~s--\::J~K~~N§22.06o18.5116.55 25.21 16.52 5.59 13.25 16.25 9.59 8.85 6.67 16.85 26.53 10.16 9.05 6.75 5.08 5.56 11.64 11.63?[~~~.-tlC::;.~~.,N§I8.31 11.47 12.52 6.23 11.91 14.76 9.00 12.79 14.02 15.76 15.94 8.16 2.51 19.01 17.47 2.53 23.39Ul-.0Remark: Node-existing total task time in each stationFigure 3 Precedence diagram of worktask in everystation in line SL - DJumal Mekanikal, Disember 2002Process and Idle Time for SL·D Line (Alternative 1)3530~ 25c120";" 15oS 10...5o1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21Station1-ProcessTime 0 IdleTime)Figure 4 Bar chart for process time and idle time for Alternative 1Process and Idle Time for SL·D Line (Alternative 2)3530125~ 20";' 15~ 105o1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21StationI_Series1 DSeries2jFigure 5 Bar chart for process time and idle time for Alternative 260Jurnal Mekanikal, Disember 2002Interaction Plot (data means) for OUTPUTLD2750'S%oc 26508l~2550•• alternative 2• alternative 110 50Coefficient of variation (per cent)Figure 6 Mean output versus coefficient of variationInteraction Plot (data means) for OUTPUTLD• alternative 2• alternative 1...-,........-,<,............<, ,-,-, ,,,........"-,".2900~ 2800Q.~0 2700z~:::l;2600250010 30Downtime (percent)Figure 7 Line design versus down time61Jumal Mekanikal, Disember 2002Interaction Plot (data means) for OUTPUTLD2750~::>0..~::>o 2700~::E2650•.....------------• alternative 2• alternative 110Total inventory8062Figure 8 Mean output versus total inventory

Improving productivity through line balancing : a case study

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Improving productivity through line balancing : a case study

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