Removing the restrictive conditions for the transition from the Kanban method to milkrun

Transcription

1 Removing the restrictive conditions for the transition from the Kanban method to milkrun Josef Babor 1 Michal Bochinský 1 Pavel Kábele 1 1 Department of industrial engineering and management University of West Bohemia in Pilsen Univerzitni 8, Pilsen, Czech Republic baborj@kpv.zcu.cz bochinsk@kpv.zcu.cz pkabele@kpv.zcu.cz Annotation: Paper aims to provide case study from logistics. Main part of paper solves problem in Kanban system. Paper describes constrain elimination in transfer from Kanban to milkrun system. This paper provides list of waste in company line material supply and paper also gives over actions for waste elimination. End of the paper lists step by step methodology for implementation of the proposed measures. 1 Introduction The concept of lean enterprise is defined 8 basic types of waste, where waste is one of excess inventory. Stocks bind together the capital, and the higher the value of stocks in a company is, the more difficult its management and administration. Of course, these findings also apply to individual sites, which constitute an essential element of the production system and the entire company. Stock levels it then affects the space requirements of workplaces and the associated handling in the workplace. The aim is therefore to minimize inventories in the workplace, provided that production is carried out smoothly and without stopping. Then it is preferable to use the system JIT, Kanban system, and milkrun system or workplace supply precise orders by "picking" from the store? At each workstation, or the material may be a way of supplying different, and it is necessary to have a combination of any suitably sweetened and suitably attached to the input stores. In a production system, you can watch two contradictory requirements, namely a high inventory at the workplace to ensure continuous production. High stocks at work will primarily appeal storekeepers who takes a large amount of material at once. However, it is not always possible carry wide variety of work and leave such a large supply, which could be up to several weeks. In the opposite direction against the idea is to reduce the space required for the storage of on-site, which leads to a possible increase in the costs of charging and also increases the risk of line stop due to lack of material to produce. To balance these two aspects is a difficult task. Solution balance of these aspects is especially in setting the right way to supply various materials consumed in the workplace. [1] Solution of supply workplaces in production is as follows: Analysis of the inventory of their relevance. Analysis of the inventory in view of their characteristics consumption. Specify how to supply. Setting procedures for supplying workplaces. The aim is to identify the significance of the material and the regularity of its consumption, it is necessary to determine the appropriate method of supply from the perspective of individual materials, workplaces and the entire production system to be effective, clear and unambiguous. By setting the appropriate method of supply is filled with the objectives of the production system, which is suitable in size and frequency of supply to ensure continuous production and minimum space requirement workplaces specified size stocks. [2] 1

2 Figure 1 Pillars of lean manufacturing [3] In the case study described in this article were conducted focus on the already established system Kanban - milkrun for 3 production lines, which are charged in three trains. Draft system as such is one of the cornerstones of lean production and this fact is shown in Figure 1. In general, setting the effective functioning milkrun is a complex process which is very complex and it is necessary to solve any adjustments together with the department of logistics, purchasing and lean. However, tension loading system using milkrun can be problematic and have your problems. In addition to problems such as that the operator loses Kanban card takes the wrong amount, noticing Kanban cards etc. may occur that will train destined for milkrun circuit overload or underload. One of the problems that need to be solve also may be the case solved in this case study. In the company was set milkrun, who suffered from the problem that occurred irregularly accumulation of large quantities of material requirements for loading up in such a way that it should train driver introduce more material than is time-consuming and physically capable. Option causes of this problem can be several, and it was therefore necessary to carry out an analysis that would identify the root cause of the problem. 2 Methodology The process solution case studies consisted primarily of two basic steps and mapping the current state by measuring the trains, which commit the material to the production line and from the analysis of circulating Kanban cards using a static simulation of five days. The last phase of the methodology is the procedure used for the implementation of the proposals into practice. The total amount of Kanban materials for each line is line 291 and various materials for the line B and the material 90 to the line C 326 materials. 2.1 Mapping of current state Mapping the current state of loading of the production lines has been done by measuring two basic parameters for the three trains, two trains of which serves only a single line or a portion thereof and one part serves two train lines. The first measured parameter on all trains was time for one circuit always measured from the exit of the train from the warehouse to the shop floor, through the loading line to complement the material in the storage and re-enter into the production hall. The second measured parameter was the amount of collected Kanban card. The record for each train was processed into a graph and a table, see. Figure 2 and Table 1 above. 2

3 Table 1 - Lab times and the amount of kanban cards for train 1 Figure 2 - Lap time and the amount collected kanban cards Output of the measurement, which was performed for a minimum of 15 lines is Table 2, which shows the minimum and maximum values of the measured parameters. Table 2 - Outputs of measurement From Table 2 it is also seen that the lap times were irregular and with large variance values as lap times and the amount of collected Kanban cards. The shortest circuit lasted five minutes and 16 seconds, in this round picked train only 2 Kanban cards (of the total 291 materials). Lap times are different and sometimes as short train operator was afraid that she got into a situation that will not prosecute introduce material on the line time and therefore prefer to ride the train often. Slow contrary, some rounds were caused by the train operator did as activities outside their job description (moving pallets, packing materials, unpacking and untangling cables, filling materials to another line and they are leaving outside of their route). Avoid this problem, especially in setting a fixed schedule for individual trains (introduction milkrun) accurate workload milk runners, training, job description and employee division between train drivers, logistics and other personnel staff on the line. 3

4 2.2 Analysis Kanban cards flow Introduction milkrun not be possible without a previous analysis and troubleshooting random accumulation loading requirements. In the case study, it was necessary to analyse the turnover time of individual Kanban cards that plays a crucial role in setting the individual filling lines. Turnaround Kanban cards has been derived based on the clock line, which is based on schedules, take into account the proportion of the left and right variations of the individual components, see Table 3, as well, was calculated by standard parts. Turnover Kanban cards ranges from 15 minutes to 53 innings. One shift lasts 7.5 hours. Table 3 - Input data in the analysis The outputs from the static simulation are presented in Figure 3 for all 3 lines. Figure 3 Outputs of simulation The graphs show that the static simulation confirmed the accumulation of requirements for loading. The graph also dashed line displayed potential maximum loading materials on line, taking into account the distribution of load trains and routes. The analysis shows that the number of Kanban cards and times of fluctuations in the exchange vary. Thus, if a situation arises where there is a fluctuation in the amount of Kanban cards may be that parts with short turnover Kanban cards will not be backfilled in time. Due to lack of priorities will not be serviced first Kanban cards with short sales will not be backfilled in time, and stops the line. 4

5 Table 4 amount of materials in risk group By this analysis, it is possible to define and filter out Kanban cards on two groups, for cards with less than 2 hours turnover and above 2 hours turnover. Two hour limit have been set like this because it is possible to asses these Kanban cards as risk group for charging part numbers cards with shorter turnover are more likely to be cause of line stopping. All of Kanban cards with turnover less than 2 hours, are counted in table 4. Just because of huge amount of data, there are not all part numbers listed. Main part of this paper / project have been setting of fixed timetable (schedule) with one lap time set to 30 minutes. Because of line productivity safety there have been set limit of 2 hours turnover to mark Kanban card with red colour (see table 4). These Kanban card need to be delivered right in the next lap after picking them from line. In the time when the milk runner have already prepared part number with main priority, than he can deliver another Kanban cards. If the milk runner doesn t have time to prepare more Kanban cards he can just deliver prepared part numbers and other part numbers can be delivered in another lap. Thanks to this adjustments we can get a new system for line supply in fixed timetable. This adjustment doesn t solve problem with Kanban card accumulation, but this adjustment can set new rules for line supply and it can stabilizes line supply with elimination of part number non delivery risk. A lower manipulation, amount of laps and energy saves have been made by these adjustments. Huge turnover time materials extraction from milkrun should be the next step, but this step is unnecessary. Next necessary step should be warehouse part number placement optimisation. Optimisation need to be done to decrease picking time for A priority part numbers. Part numbers with a priority (high risk materials) should be situated closer to the enter from shop floor and part numbers with lower turnover rate should be situated closer to the exit from warehouse to shop floor. Alternatives for this adjustments which can eliminate accumulation of Kanban cards can be: Electronic Kanban Volume based schedule of line supply Or single bin line supply However, all of these alternatives will bring higher investment and complete line supply redesign. 2.3 Putting the procedure into practice 1 st step for putting the adjustments into practice is Kanban card visual, red colour trim for part numbers from high risk group of part numbers. 2 nd step is installation of Kanban card holder bin on the milkrun train for collecting of high and low risk materials. 3 rd step should be line supply process adjustment, choice of pilot line, staff training for pilot line trial operation and creation of finished product inventory on the pilot line. 4 th step should be testing of pilot trial operation. One line should be selected so as not to jeopardize the smooth running of the production, and a crisis plan for loading the material onto the line (the firefighter who would run with the material on the line) should be prepared. 5

6 5 th step should be a trial operation analysis, a workshop with logistics staff, lean and milk runners themselves from pilot operations. Troubleshoot any problems and train all train staff. 6 th step should be the test operation on all lines should be carried out again with the support of the fire brigade who would run with the material on the line. 7 th step should be an evaluation of all lines trial operation and possible adjustment of the quantity of materials in the risk group. 8 th step is complete implementation of milkrun method and continuous improvement. 3 Conclusion The proposed solution, which takes into account the analysis and own observations, includes: setting a fixed cycle length of 30 minutes for all trains, which will increase electricity savings, reduce wheelchair wear and train energy; Fixing a fixed workload for the trainer during a shift to avoid unnecessary fluctuations within the loading cycle; Identification of material with short turn-around Kanban card (KK 2 hours); To highlight priority (highspeed) parts and Kanban cards in the system, for example using red color; The distribution of boxes that serve to collect Kanban cards on the wheelchair on the priority (red) and standard. Another procedure for the company would be to reorganize the stock in the warehouse so that the priority materials are at the train's entrance to the warehouse (for example, based on the ABC analysis according to the frequency of their loading). Recommendations in addition to the case study were, for example, a snapshot of trainers' work on which further wastage should be identified, setting clear load processes, restoring workloads for trainers and other logistics staff, possibly adjusting the number of items for some materials, and post- System to adjust the amount of materials in the risk group (for example, reduce the risk group to 1.5 hours, possibly even 1 hour after stabilization). Alternatively, specify another group of materials, namely the materials that have to be loaded at the end of the shift (thus 3 groups of materials according to the turnover time), to be marked with a green stripe - only if corrective mops are not sufficient. The conclusion of the article contains a methodology for putting the proposed solution into practice. References [1] ŠIMON, M., TRNKOVÁ, L. Logistika - teoretická část. 1. vyd. Plzeň : SmartMotion s.r.o., 2013, ISBN: [2] EDL, M., KUDRNA, J. Metody průmyslového inženýrství. 1. vyd. Plzeň : Smart Motion, s.r.o., 2013, ISBN: [3] citynetevents [Online] 2015 [Cit. 3 srpen 2016] Dostupné z: 6