Search results

This paper studies organizational change following a shift in an industry environment, in the context of how a focused factory adapts to a change in its manufacturing objectives. We use the organizational nature of production operations to suggest that the effectiveness of adaptation will depend on how well the manufacturing requirements of the new objectives match manufacturing capabilities at the production line level. We test our hypotheses using primary data from the Hartselle, Alabama compressor manufacturing focused factory of the Copeland Corporation. The results suggest that factors that influence adaptability derive from individual and organizational competence, and that the direction and extent of their influence depends on the systemic nature of the operational activity concerned. The results highlight roles of carefully designed complexity in operations and of process-oriented decision making on the shop floor in successful adaptation. This work contributes to our understanding of how business organizations overcome constraints to change.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

Presents a linear goal programming (LGP) model, which can be used to derive an optimal daily production schedule for JIT production systems. Also provides an explanation of how a detailed post‐optimal LGP analysis can enable a decision maker to examine the effects of production scheduling in a JIT “mixed‐model” production environment. To illustrate the informational efficacy of the proposed JIT‐based LGP model, presents an illustrative example.

This paper aims to provide feasible countermeasures for the application of lean manufacturing in automatic sand casting workshops to optimize production line balance.

A production line balance optimization model for sand casting workshops is proposed. The value stream mapping (VSM) approach is applied to diagnose the problems in the production process. An optimization scheme is established based on eliminate, combine, rearrange, simplify and increase theory and Kanban management method. Further, simulation is done to compare current VSM and future VSM.

After implementing the proposed model, findings indicated that the idle time of equipment was effectively reduced, the line of balance of the production line was increased by 44.7%, the production lead time was shortened by 60.3% and the production capacity was increased by 50.0%.

Application of the optimization model in this study is limited to sand casting workshops that have realized automatic or semi-automatic production.

This paper provides an optimization model for the implementation of lean manufacturing in sand casting workshops and provides a reference case that reflects the actual application of lean manufacturing tools in a real situation.

The purpose of this paper is to investigate the process optimization of a precast concrete component production line by using value stream mapping.

This paper is an empirical focused on of lean production theory and value stream mapping. The data in the case study were collected in real time on-site for each process during the production process of a prefabricated exterior wall.

The results of the current value stream map indicate that the main problems of the current production process are related to equipment, technology and organization. The equipment problems include simple demolding and cleaning tools and the lack of professional transfer channels. The technology problems include the lack of a marking mechanism and pipeline exit mechanism. There is a lack of standard operating procedures and incomplete process convergence. A comparison and analysis of the current value stream and the future value flow indicate that optimizations of the process flow, the production line layout, and the standard operating procedures have shortened the delivery cycle, reduced the number of workers, improved the operator’s operating level and balanced the production line.

The results of this study provide practitioners with a clear understanding of the optimization of the precast concrete component production and represent a method and basis for the process optimization of a factory production line; the approach is suitable for process optimization in other areas.

This research represents an innovative application of lean production theory and value stream mapping in a complex production line of precast concrete components and thereby fills the gap between the theory and practice of the optimization of a precast concrete component production line.

In this article a case study is reported which deals with identifying the sources of downtime, and a procedure which could help management to predict whether the daily production standards in auto assembly‐line operations could be met given the intensity of sources of downtime. This study was conducted for a large auto engine manufacturer. The engine assembly line under study is subject to good preventive maintenance to avert unexpected breakdowns that would shut down the line or lower the quality so as to reduce the yield in total. Two multivariate statistical procedures are used – factor analysis and multiple discriminant analysis.

Reducing production auxiliary time is the key to improve the efficiency of the existing mixed-flow assembly line. This paper proposes a method combining improved genetic algorithm (GA) and Flexsim software. It also investigates mixed-flow assembly line scheduling and just-in-time (JIT) parts feeding scheme to reduce waste in production while taking the existing hill-drop mixed-flow assembly line as an example to verify the effectiveness of the method.

In this research, a method is presented to optimize the efficiency of the present assembly line. The multi-objective mathematical model is established based on the objective function of the minimum production cycle and part consumption balance, and the solution model is developed using multi-objective GA to obtain the mixed flow scheduling scheme of the hill-drop planter. Furthermore, modeling and simulation with Flexsim software are investigated along with the contents of line inventory, parts transportation means, daily feeding times and time points.

Theoretical analysis and simulation experiments are carried out in this paper while taking an example of a hill-drop planter mixed-flow assembly line. The results indicate that the method can effectively reduce the idle and overload of the assembly line, use the transportation resources rationally and decrease the accumulation of the line inventory.

The method of combining improved GA and Flexsim software was used here for the first time intuitively and efficiently to study the balance of existing production lines and JIT feeding of parts. Investigating the production scheduling scheme provides a reference for the enterprise production line accompanied by the quantity allocation of transportation tools, the inventory consumption of the spare parts along the line and the utilization rate of each station to reduce the auxiliary time and apply practically.

The purpose of this paper is to adopt the total productive maintenance (TPM) in the food industry and especially in bakery products. The paper aims to develop a methodology for increasing production rate, improving the quality of the products and providing a healthier and safer work environment.

The methodology is based on analysing the reliability data of an automatic production line. It is divided into four steps, whose aims are to bring forth improved maintenance policies of the mechanical equipment. Also, the continuous and thorough inspection of the production process is achieved through measurements of the overall equipment effectiveness (OEE).

The goal of development methodology is to bring competitive advantages, such as: increasing the productivity; improving the quality of the products; and reducing the cost production of the line.

The development methodology in the food industry increases the production rate, improving the quality of the products and providing a healthier and safer work environment. It can be useful to guide food product machinery manufacturers and bread and bakery products manufacturers to improve the design and operation of the production lines that they manufacture and operate.

This paper presents the implementation of TPM in a pizza production line and, using certain assumptions, the generalization of the results in bakery production lines.

Garment manufacturing is a traditional industry with global competition. The most critical part is streamline, as it generally involves a great number of operations. The purpose of this paper is to, based on the model of group technology (GT), sum up the methods of assembly line optimization to optimize the streamline, so that the machines of the workstation can perform the assigned tasks with a balanced loading.

In this paper, the methods of obtaining and optimizing data includes literature, research and optimization methods of basing on GT model. The main direction of literature has two aspects: Lean production theory and streamline assignment. Research mainly concludes three aspects: research place, research object and the research content. The method of time determination is averaging the testing values of repeated measurements. Optimization methods of basing on GT model mainly include combination of the same type of technologic processes in sequence, combination of independent branch process, the combination of mainstream and branch processes and offside combination of the same type of processes.

After optimization, in the utilization rate of equipment: hanging system ratio was increased from 22.95 to 62.12 percent, which greatly improved the utilization rate of enterprise equipment. In equipment layout: hanging equipment layout was turned linear type into “U” type, which realized the synchronization of production. GT model will be well applied in the garment production streamline. Compared with other enterprises, A company has large garment hanging system, which reflects the advanced, comprehensive, representative. Therefore, the paper applied optimization methods to trousers, production efficiency has been improved greatly, the utilization rate of equipment is promoted and reworking phenomenon is reduced greatly.

Through the optimization of the production process and equipment layout, the A company’s compiling efficiency has been greatly improved, but how can the system become computerized, accurately and intelligence, which has been an important direction of research now.

By optimizing, it is fully proved that applying GT to the streamline optimization is feasible. GT is an important branch of Lean production, summing up the optimization methods basing on the GT model to optimize the streamline not only enriches the relevant theory research, but also provides a theoretical basis for the practical production. GT model not only can be used in the shirt production process, as for other production processes, for example, trousers, skirts can also be widely applied, which realizes the theory application in the practical production.

The originality of this paper is that through the analysis of the model of GT, the paper sums up the methods of assembly line optimization to optimize the streamline. Although the model of GT is used widely in electronics, automobile and industry, it is relatively weak in the optimization of garment production line, there are not many literatures on practical application of group technology in the clothing. Besides, the paper is applied to practical production, which not only can improve production efficiency, but also make the theoretical research have basis and combine the theory and practical production.

The purpose of this paper is to construct a task assignment model for U-shaped production lines with collaborative task, which is optimized by minimizing the number of workers and balancing the workload of the operators. The ultimate goal is to increase productivity by increasing the U-line balance and balancing the load on the operators.

First, task selection and update mechanism are analyzed and the task selection mechanism suitable for collaborative task is proposed. Second, M-COMOSAL is obtained by improving the original COMOSAL. Finally, The M-COMOSAL algorithm and the COMAOSAL algorithm are used to perform job assignment on the double-acting clutch U-shaped assembly line.

According to the allocation scheme obtained by M-COMSOAL, the beat can be adjusted according to the change of order demand. The final allocation scheme is superior to the COMSOAL algorithm in terms of number of workers, working time, production tempo and balance rate. In particular, compared with the old scheme, the new scheme showed a decrease of 16.7% in the number of employees and a 18.8% increase in the production line balance rate. Thus, the method is helpful to reduce the number of operators and balance the workload.

The new algorithm proposed in this paper for the assignment of collaborative task can minimize the number of workers and balance the load of operators, which is of great significance for improving the balance rate of U-shaped production lines and the utilization of personnel or equipment.