Line Balances Research Articles

Analisis Efisiensi Waktu Siklus Untuk Meningkatkan Produktivitas Dengan Line Balancing Pada Proses Pengemasan Produksi Obat Diabetes di PT.OPQ

Operation Excelence is needed at manufacturing process in order to achive optimum cost. One of method is using line balancing. It work by increasing efficiency and remove bottole neck at workstation.. The purpose of this research is to increase productivity in the work path of diabetes drug production line, it means that all work stations can achieve optimum output, eliminate or reduce material accumulation by identifying line balances at work stations. By using the Line Balancing method. The method used is the Ranked Position Weight (RPW) heuristic method. As result productivity was increasing, with line efficiency from 58.36% to 80.25%, balance delay from 41.64% to 19.75%, a decrease in the amount of material accumulation between work stations on the diabetes drug production trajectory from 25 - 1175 doos / hour to 4 - 174 doos / hour, and eliminating the bottleneck on the trajectory of diabetes drug production.

Using REIT Follow-on Equity Offerings to Pay down Credit Line Balances: Bank Certification or Monitored Financial Flexibility?

Using hand collected data from offering prospectuses and other corporate filings, we examine the market response to real estate investment trust (REIT) follow-on stock offerings’ stated uses of proceeds. We also track REIT banking relationships over time. Consistent with the idea of bank certification, we show that markets react relatively favorably to REIT equity offers where issuers have lending relationships with affiliates of the underwriters. However, we also find that reactions are most favorable where REIT issuers intend to repay their bank’s line of credit, regardless of the bank’s affiliation with the underwriters. This pattern is particularly strong among smaller firms with lower institutional ownership. We posit that credit line repayments preserve benefits of bank monitoring while enhancing financial flexibility. Further examination reveals that this monitored financial flexibility is the dominant effect.

Fitness landscape analysis of the simple assembly line balancing problem type 1

As the simple assembly line balancing problem type 1 (SALBP1) has been proven to be NP-hard, heuristic and metaheuristic approaches are widely used for solving middle to large instances. Nevertheless, the characteristics (fitness landscape) of the problem’s search space have not been studied so far and no rigorous justification for implementing various metaheuristic methods has been presented. Aiming to fill this gap in the literature, this study presents the first comprehensive and in-depth Fitness Landscape Analysis (FLA) study for SALBP1. The FLA was performed by generating a population of 1000 random solutions and improving them to local optimal solution, and then measuring various statistical indices such as average distance, gap, entropy, amplitude, length of the walk, autocorrelation, and fitness-distance among all solutions, to understand the complexity, structure, and topology of the solution space. We solved 83 benchmark problems with various cycle times taken from Scholl’s dataset which required 83000 local searches from initial to optimal solutions. The analysis showed that locally optimal assembly line balances in SALBP1 are distributed nearly uniformly in the landscape of the problem, and the small average difference between the amplitudes of the initial and optimal solutions implies that the landscape was almost plain. In addition, the large average gap between local and global solutions showed that global optimum solutions in SALBP1 are difficult to find, but the problem can be effectively solved using a single-solution-based metaheuristic to near-optimality. In addition to the FLA, a new mathematical formulation for the entropy (diversity) of solutions in the search space for SALBP1 is also presented in this paper.

Using REIT Follow-on Equity Offerings to Pay Down Credit Line Balances: Bank Certification or Monitored Financial Flexibility?

Using REIT Follow-on Equity Offerings to Pay Down Credit Line Balances: Bank Certification or Monitored Financial Flexibility?

Analisis cycle time proses perakitan senjata di PT Pindad (Persero)

This paper aims to analyze the cycle time of the assembly line of one of the weapons products at PT. Pindad (Persero) and to explore the effective methods to improve its performance. The method used is a quantitative analysis of assembly data involving 155 components and 56 tasks distributed over 43 work stations, accompanied by document analysis, especially on scientific literature, to elaborate various appropriate methods to become solutions to the problems encountered. The results show that almost all workstations had a cycle time greater than the takt time. It is also known that there is an imbalance of existing workstations, with the lightest workload lasting 67 seconds while the largest workload lasting 253 seconds. The results of the elaboration of the literature show that several potential methods can provide solutions to the problems encountered by considering the characteristics of the assembly line with a straight-line configuration. This study contributes to the literature by analyzing cycle times and assembly line balances in the defense industry relatively rarely studied in Indonesia.

Paying dividends: Cash or credit?

This paper examines to what extent firms utilize lines of credit to fund cash dividends. We find that higher dividend payouts are related to higher liquidity and that dividend-paying firms who experience cash shortages will utilize credit lines to continue dividend payments. Additionally, we show that credit lines are a permanent component of dividend-paying firms’ capital structure. Our sample statistics indicate that dividend-paying firms are considerably different than non-dividend-paying firms. Dividend payers tend to be more liquid despite having less cash, have smaller credit line balances, have higher market capitalizations, have less long-term debt, are more profitable, and spend less on capital investments. We conclude that access to credit lines is an important component of dividend-paying firms’ capital structure while the level of cash is not.

A Case Study in Line Balancing and Simulation

Assembly line balancing (ALB) allocates individual tasks to work stations while respecting the physical, safety, and quality constraints. Two-sided assembly lines are generally used in the production of medium or large-sized products (e.g. automotive, household appliance). We considered several characteristics including zoning constraints, the task to task relationships, tooling and station dependent constraints to offer the real-world environment. The most common two objectives for the ALB are minimizing the number of workers (type-1) and minimizing the cycle time (type-2). This article presents an integer programming formulation for both type-1 and type-2 ALB problems and metaheuristics to solve this complex problem. Even if ALB gives better results than the current line balance that our industry partner applied, it cannot be guaranteed that the amount of daily production will increase due to randomness in the line. We simulate the proposed line balances to provide a testing platform for line balancing results and to help identify inefficiencies and bottlenecks in the system.

The stability radius of an optimal line balance with maximum efficiency for a simple assembly line

We consider a simple assembly line balancing problem in which each element of the partially ordered set of assembly operations must be assigned to one element of the set of workstations used for processing the operations. An objective is minimizing the product of the number of workstations used in the line balance and the cycle time of the line balance among all admissible line balances. An admissible line balance is a partition of all assembly operations into at least two workstations without violating the precedence relations among the assembly operations. We assume that during the lifespan of the assembly line, the duration of each manual operation may deviate from an initially estimated value, while the duration of each automated operation is deterministic. We conduct the stability analysis of an optimal line balance. First, we derive a sufficient and necessary condition for an optimal line balance to be stable. Second, we show that the stability radius of an optimal line balance could be infinitely large. We also establish some lower and upper bounds for a finite stability radius. Third, we derive formulae that are needed and develop an algorithm for obtaining the stability radius of an optimal line balance.

Stability radii of optimal assembly line balances with a fixed workstation set

For an assembly line, it is required to minimize the line's cycle time for processing a partially ordered set of the assembly operations on a linearly ordered set of the workstations. The operation set is partitioned into two subsets, manual and automated. The durations of the manual operations are variable and those of the automated operations are fixed. We conduct a stability analysis for this problem. First, we derive a sufficient and necessary condition for the optimal line balance to have an infinitely large stability radius. Second, we derive formulas and an algorithm for calculating the stability radii for the optimal line balances. Third, we report computational results for the stability analysis of the benchmark instances. Finally, we outline managerial implications of the stability results for choosing most stable line balances, which save their optimality in spite of the variations of the operation durations, and for identifying the right time for the re-balancing of the assembly line.

Enumerations and stability analysis of feasible and optimal line balances for simple assembly lines

For a simple assembly line, it is necessary to minimize a number of the workstations for processing a partially ordered set of the tasks V={1,2,…,n} within a fixed cycle time (such a problem is denoted as SALBP-1). A dual assembly line balancing problem denoted as SALBP-2 is to minimize a cycle time provided that a number of the workstations is fixed. An initial vector t=(t1,t2,…,tn) of the processing times of the tasks V is given for both problems SALBP-1 and SALBP-2. For a subset V∼⊆V of the manual tasks j∈V∼, the processing times tj may vary since operators may have different skills, levels of fatigue, experience, and motivation. For any automated task i∈V⧹V∼, the processing time ti cannot vary. We investigate a stability of an optimal line balance for the assembly line with respect to variations of the processing times of the manual tasks (a line balance is stable, if it is optimal for any sufficiently small variation of the processing times). We developed the enumerative algorithms for constructing feasible and stable optimal line balances for the problem SALBP-1 and those for the problem SALBP-2. Computational results for the stability of the assembly line balances showed that there are a lot of unstable optimal line balances for the tested benchmark assembly lines. The simulation for the benchmark assembly line showed that the stable optimal line balance considerably outperforms the unstable ones. The complexity analysis of the assembly line balancing problems with different partial orders given on the task set V has been developed.

Multiple-source learning precedence graph concept for the automotive industry

In modern production systems, customized mass production of complex products, such as automotive or white goods, is often realized at assembly lines with a high degree of manual labor. For firms that apply assembly systems, the assembly line balancing problem (ALBP) arises, which is to assign optimally tasks to stations or workers with respect to some constraints and objectives. Although the literature provides a number of relevant models and efficient solution methods for ALBP, firms, in most cases, do not use this knowledge to balance their lines. Instead, the planning is mostly performed manually by numerous planners responsible for small sub-problems. This is because of the lack of data, like the precedence relations between the tasks to be performed. Such data is hard to collect and to maintain updated.Klindworth, Otto, and Scholl (2012) proposed an approach to collect and to maintain the data on precedence relations between tasks at a low cost, as well as to produce new high-quality feasible assembly balances based on this data. They utilize the knowledge on former production plans available in the firm. However, due to reliance on the single source of information, their concept needs long warming-up periods. Therefore, we enhance the concept by incorporating multiple sources of information available at firms, as the modular structure, and present guidelines on how to conduct valuable interviews. The proposed interview enhancements improve the achieved results significantly. As a result, our approach generates more efficient new feasible assembly line balances without requiring such long warming-up periods.

Stable optimal line balances with a fixed set of the working stations

A simple assembly line balancing problem is considered provided that number m of working stations is fixed. In such a problem, denoted as SALBP-2, it is necessary to minimize a cycle time for processing a partially ordered set of operations V = [1, 2,…, n] on a set of m linearly ordered (working) stations. An initial vector of the processing times t = (t1, t2,… ,tn) of the operations V is given. And for each automated operation processing time ti cannot vary during a life cycle of the assembly line. For a subset V V of the manual operations j ∈ V, processing times tj may vary, since different workers may have different skill, experience, etc. We investigate a stability of the optimal line balance of the simple assembly line with respect to simultaneous variations of processing times tj of manual operations j ∈ V. An optimal line balance is stable if its optimality is preserved for any sufficiently small variations of processing times tj, j ∈ V. We propose an enumerative algorithm and a program in C++ for constructing all the stable optimal line balances for the problem SALBP-2. Computational results for the modified benchmark instances have been presented.

Task-failure-driven rebalancing of disassembly lines

Many reverse-logistics systems that collect and reprocess end-of-life products require a disassembly stage. The variability of incoming products and the extent of damage, which is more likely to occur during disassembly than assembly, create significant uncertainty in disassembly tasks, namely the possibility of failed tasks. Such failures may lead to some successor tasks being infeasible, which changes the work content of downstream stations. To improve the profitability of such a disassembly line, a mixed-integer-programming-based, predictive-reactive approach is proposed. In the first step, a predictive balance is created and then, in the second step, given a task failure, the tasks of the disassembled product with that task failure are re-selected and re-assigned to the stations (i.e. the line is rebalanced). In the second step, the objective function models both the profit obtained from the disassembled product and the possible increase in any station's workload beyond the predictive cycle time. Since this rebalancing approach affects the work content of stations, a discrete-event simulation study is also carried out to analyse and compare the performance of disassembly lines for optimally found line balances (predictive and reactive). The results show that, with the proposed approach, 24–32% of the monetary throughput lost due to not taking corrective action can be recovered.

On a learning precedence graph concept for the automotive industry

Assembly line balancing problems (ALBP) consist in assigning the total workload for manufacturing a product to stations of an assembly line as typically applied in automotive industry. The assignment of tasks to stations is due to restrictions which can be expressed in a precedence graph. However, (automotive) manufacturers usually do not have sufficient information on their precedence graphs. As a consequence, the elaborate solution procedures for different versions of ALBP developed by more than 50 years of intensive research are often not applicable in practice. Unfortunately, the known approaches for precedence graph generation are not suitable for the conditions in the automotive industry. Therefore, we describe a new graph generation approach that is based on learning from past feasible production sequences and forms a sufficient precedence graph that guarantees feasible line balances. Computational experiments indicate that the proposed procedure is able to approximate the real precedence graph sufficiently well to detect optimal or nearly optimal solutions for a well-known benchmark data set. Even for additional large instances with up to 1,000 tasks, considerable improvements of line balances are possible. Thus, the new approach seems to be a major step to close the gap between theoretical line balancing research and practice of assembly line planning.

Incorporating physical demand criteria into assembly line balancing

Many assembly line balancing algorithms consider only task precedence and duration when minimizing cycle time. However, disregarding the physical demands of these tasks may contribute to the development of work-related musculoskeletal disorders in the assembly line workers. Three line balancing heuristics that incorporate physical demand criteria were developed to solve the problem of finding assembly line balances that consider both the time and physical demands of the assembly tasks: a ranking heuristic, a combinatorial genetic algorithm, and a problem space genetic algorithm. Each heuristic was tested using 100 assembly line balancing problems. Incorporating physical demands using these algorithms does impact the assembly line configuration. Results indicated that the problem space genetic algorithm was the most adept at finding line balances that minimized cycle time and physical workload placed upon participants. Benefits of using this approach in manufacturing environments are discussed.

Assembly Line Balancing Using Genetic Algorithms with Heuristic-Generated Initial Populations and Multiple Evaluation Criteria

We use genetic algorithms (GA) to solve the assembly line balancing (ALB) problem. Inparticular, we show how this technique can be used to generate feasible line balances, improve upon solutions obtained by other heuristics reported in the literature, and utilizeany one or more evaluation criteria that can be expressed in functional form. The procedure is demonstrated with two examples: (1) intimating the improvement of heuristic-generated ALB solutions by including them in the GA initial population, and (2) the possibility of balancing assembly lines with multiple criteria and side constraints. These examples suggest that GA can be a powerful tool in ALB. To investigate the utility of GA on single-criterion problems, an experiment is conducted that compares both the GA approach and conventional heuristics. Results indicate that the GA solutions are significantly improved over the heuristic solutions under the conditions studied. It is also found that the presence of heuristic-generated conventional solutions in the GA initial population leads to statistically preferred results.

Finding optimal line balances with OptPack

This paper describes OptPack, a new algorithm for finding optimal solutions to assembly line balancing problems. Preliminary computational experience shows that the algorithm is significantly faster, on the benchmark literature problems, than Johnson's (1988) Fable, the fastest currently available algorithm. A microcomputer implementation of OptPack is also described and computational experience is reported.

A goal approach to assembly line balancing

A zero-one goal programming model for the assembly line balancing problem is developed. The goal model provides increased flexibility in constructing line balances by simultaneously considering varying operational requirements, such as zoning, sequencing, idle time, cycle time and costs. A sensitivity analysis of an example model highlights the usefulness of the approach in the planning stages of a line balance development.

An Integer Programming Algorithm with Network Cuts for Solving the Assembly Line Balancing Problem

In this paper, we describe an integer programming algorithm for assigning tasks on an assembly line to work stations in such a way that the number of work stations is minimal for the rate of production desired. The procedure insures that no task is assigned to a work station before all tasks which technologically must be performed before it have been assigned (precedence restrictions are not violated), and that the total time required at each work station performing the tasks assigned to it does not exceed the time available (cycle time restrictions are not violated). The procedure is based on a systematic evaluation (enumeration) of all possible task assignments to work stations. Significant portions of the enumeration process are performed implicitly, however, by utilizing tests described in the paper which are based on the specific structure of the line balancing problem. An artifice termed a network cut is also developed which eliminates from explicit consideration the assignment of tasks to work stations where such assignments would not lead to improved line balances. Results reported demonstrate that the procedure can obtain optimal balances for assembly lines with between 50 and 100 tasks in a reasonable amount of computation time and with modest computer storage requirements.

Assembly Line Balancing with a Precedence Matrix

Assembly line balancing consists of assigning work elements, which are subject to sequencing restrictions, along an assembly line in an optimal manner. The procedure presented in this paper leads to optimal line balances by operation on a matrix of zeros and ones called a “Precedence Matrix.” A nine element problem is used to illustrate the method in detail and comparisons with other procedures are made. Several balances obtained by applying the FORTRAN program appended to the paper to actual and sample problems are also shown.