Analisis Keseimbangan Lini dalam Proses Produksi Roti Tawar di PT Nippon Indosari Corpindo – Cikarang
Abstract
The high growth rate in particular industries based on agriculture is followed by the development of increasingly advanced technology, will lead into a global competition and the existing problems in industries become more complex. In facing these industrialized world problems and global competition, accurately efficiency, effectiveness, and productivity are the key factors to be able to compete competitively for each agro-based industry. One of the effort that can be done to support is with some planning and designing of appropriately production systems with a continue production line balancing that influenced by operator performance, properly layout, and also the production queuing. The purpose of this research was to determine the standard working time on a number of work components that be involved in the process of white bread production, to analyze the layout, and to analyze the performance of queuing system in white bread production line that already exist. Working time measurement used to determine the standard working time by using the Westinghouse method in determining the value of adjustments and looseness. The layout analysis was analyzed by determining the level of activity relationship, total closeness rating, and activity relationship chart. Queuing analysis was done by forming a model that consisted of two types, namely material flow balancing analysis and Monte Carlo queuing simulation technique. Monte Carlo simulation technique used to obtain entity in the form of customer analysis, server analysis, and queue analysis, which are customer analysis consisted of number of finished, average waiting time (Wq), and average cycle time (W); server analysis consisted of server utilization; and queue analysis consisted of average queue length (Lq), and average waiting time (Wq). Production process in PT Nippon Indosari Corpindo was done by involving the cooperation between machines and operators which was deterministic and probabilistic. Work measurement was useful in determining the standard working time, layout analysis and queuing analysis. Time measurement was done by using the stopwatch method to the operator to determine the standard time, where the standard time that obtained from the calculation is in the amount of 8.45 hours for 1 batch (443.5 kg) of bread dough production. White bread production line at the PT Nippon Indosari Corpindo had a product layout which adjusted by its production process with have a straight line shape workmanship. Based on the analysis using the Analysis Relationship Chart, the formation changing in Raw Material and Mixing Department was needed. Its changing be based on sequence of work flow; efficiency of distance, time, and work; temperature, noise; level of comfort; ease of surveillance; and the existing of communication / work control paper. The highest value of Total Closeness Rating was Packing department (176), followed by Crating (168), Mixing (165), Oven (164), Raw Materials (92) and Finish Good department (87). The changing were made in the context of efficiency of time, distance, and packaging material transferring cost from Raw Material department onto Packing department which have a far distant. Queue analysis carried out by forming a queuing models which were divided into 9 queue model, they were Model A with a material flow balancing analysis at Mixing Sponge station, Model B with a material flow balancing analysis at Fermentation 1 station, Model C with a material flow balancing analysis at Mixing Dough station, Model D with a queuing simulation technique at Dividing and Rounding station, Model E with a queuing simulation technique at Panning and Racking station, Model F with a material flow balancing analysis at Fermentation 2 station, Model G with a queuing simulation technique at Tray Closing station, Model H with a queuing simulation technique at Depanning station, and Model I with a queuing simulation technique at Trimming, Packaging, and Crating station. Based on the results of material flow balancing and queuing simulation, Model A showed no queue of material lined up, with the machine utility level was 39.00% and the value of idle time each day was 61.00%. The low value of the machine’s utility model related to the time balancing with other stations. Model B showed no queue of material lined up, with the first fermentation room utility level was 94.00% and the value of idle time each day was 6.00%. Model C showed no queue of material lined up, with the machine utility level was 98.00% and the value of idle time each day was 2.00%. The high utility in this model associated with the time of distance per batch which was adjusted to the productive time per batch at this station. Model D showed the waiting material and time were none, with the machine utility level was 90.94%. Model E showed the waiting material and time were none, with the operator utility level was 92.41%. Model F showed no queue of material lined up, the second fermentation room utility level was 83.00% and the value of idle time for each day was 17.00%. Model G showed the waiting material and time were none, with the service utility level was 49.93%. Model H showed the waiting material and time were none, with the machine utility level was 83.50%. And the Model I showed the waiting material and time were none, with the overall utility’s value was 92.92%. Mean equality tests (t test) was done by comparing the simulation results with the historical data obtaining, where was found that the service time of each station had a P value greater than 5% (P> 0.05) or outside the critical area with a 95% confidence level (α = 5%). This showed the uniformity between service time’s mean value on the real conditions with the results of simulation shown, indicated that simulation resulted could be said to be valid for use in simulation models.