Production Line Balancing Research Articles

Balance Analysis and Improvement of Flywheel Production Line

It studies the balance problems of cycle time of a flywheel production line in this paper. Based on the working time measured using lean manufacturing (LP) methods, the bottleneck processes of production line are found by simulating with software Witness, which is improved by using production cycle balancing method. Comparing the relevant parameters before and after the production line balance,the improvement results of production line are significant and the production efficiency can be improved.

Optimal Inspection Allocation Decision with Production Line Balance in Multi-Station Assembly Systems

This paper explores the inspection allocation problem with considering production line balance at the same time for multi-station assembly systems. A mathematical model is developed in order to find the minimal total cost. When the number of parts increases, the time spent increases dramatically with the enumerative method. Therefore, an approach to genetic algorithm is developed and it takes much less time with near-optimal solutions.

A cost evaluation method for dynamic line balancing

AbstractA procedure is presented for calculating stochastic costs, which include operator (labor) and inventory costs, associated with dynamic line balancing. Dynamic line balancing, unlike the traditional methods of assembly and production line balancing, assigns operators to one or more operations, where each operation has a predetermined processing time and is defined as a group of identical parallel stations. Operator costs and inventory costs are stochastic because they are functions of the assignment process employed in balancing the line, which may vary throughout the balancing period, and the required flow rate. Earlier studies focused on the calculation of the required number of stations and demonstrated why the initial and final inventories at the different operations are balanced.The cost minimization method developed in the article can be used to evaluate and compare the assignment of operators to stations for various assignment heuristics. Operator costs and inventory costs are the components of the cost function. The operator costs are based on the operations to which operators are assigned and are calculated for the entire work week regardless of whether an operator is given only a partial assignment which results in idle time. It is assumed that there is no variation in station speeds, no learning curve effect for operators' performance times, and no limit on the number of operators available for assignment. The costs associated with work‐in‐process inventories are computed on a “value added” basis. There is no charge for finished goods inventory after the last operation or raw material before the first operation.The conditions which must be examined before using the cost evaluation method are yield, input requirements, operator requirements, scheduling requirements and output requirements. Yield reflects the output of good units at any operation. The input requirement accounts for units discarded or in need of reworking. The operator requirements define the calculation of operator‐hours per hour, set the minimum number of operators at an operation, and require that the work is completed. The scheduling requirements ensure that operators are either working or idle at all times, and that no operator is assigned to more than one operation at any time. The calculation of the output reflects the yield, station speed, and work assignments at the last operation on the line.An application of the cost evaluation method is discussed in the final section of the article. Using a simple heuristic to assign operators, the conditions for yield, inputs, operators, scheduling, and output are satisfied. The costs are then calculated for operators and inventories.In conclusion, the cost evaluation method for dynamic balancing enables a manager to compare the costs of assigning operators to work stations. Using this method to calculate the operator and inventory costs, a number of different heuristics for assigning operators in dynamic balancing can be evaluated and compared for various configurations of the production line. The least cost solution procedure then can be applied to a real manufacturing situation with similar characteristics.

A simulation approach for adapting a production line balancing procedure to a probabilistic environment

Abstract Many of the line balancing procedures at present available have several limiting characteristics. First, they often tend to be based on approaches that encompass deterministic operating parameters when, in fact, realistic production systems have probabilistic operating parameters. Secondly, they are often applicable only to small noncomplex production lines. It is the purpose of this paper to demonstrate how Q-GERT network modelling and simulation can be employed to ascertain the effect of these realistic operating conditions on a line balancing procedure. Once such effects have been determined it will be shown how simulation can be used to adapt the line balancing procedure to realistic operating conditions.

A Method for Production Line Balancing : Assigning Works to Multi-Workers in Each Station for Higher Productivity

生産率のより高い生産工程の構成のため, まず第1段階として同一工程へ複数人員の割り当てを許し, 多段階の工程時間の制約のもとで作業の工程配分を行う. つぎに第2段階として各工程において, 複数人員へ要素作業を単位としてなるべく各人が同一の要素作業を受け持つように作業を割り付ける. その際, 作業の先行関係(前進配分法)と後続関係(後退配分法)とに基づく構成結果から, 改良解を求める手法を提案した.

An Experimental Investigation and Comparative Evaluation of Production Line Balancing Techniques

Although computationally feasible optimizing algorithms for solving the production line balancing problem have not been found, a number of computational techniques have been devised and used to obtain solutions which are not necessarily optimal solutions but are hoped to be good solutions. In the study the most prominent of these techniques are examined and compared by applying them to a sample of production line balancing problems. The maximum output rate attained for a specified line length is used as the measure of effectiveness and the computing time required to make line balancing calculations for a specified output rate is used as the measure of cost. The central results of the study show that there are significant differences among the effectiveness results achieved by the line balancing techniques. Although the differences are not large, there are few changes in the relative effectiveness of the computing techniques over the range of line lengths, partial ordering strengths, and problem sizes that were investigated. For the larger problems the computing time differences are significant and in some instances are a more important consideration in the relative evaluation of the computing techniques than are the effectiveness results.