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Automated line is widely applied in industry especially for mass production with less variety product. Productivity is one of the important criteria in automated line as well as industry which directly present the outputs and profits. Forecast of productivity in industry accurately in order to achieve the customer demand and the forecast result is...
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Citations
... The output after program run is shown in Fig. 13. It is important to mention that there are other parameters [31] that could be specified in the process of decorating the pie visualization. One of such parameters is the "explode". ...
Scientific Visualization remains an integral and inevitable part of every meaningful scientific, industrial and academic research. The focus of this study is to demystify the evolution, design and programmatic construction of scientific visualizations. Real life demonstrations have been achieved in this work using Python Programming Language. This work begins by exploring the programming environment based on a Python Integrated Development Environment (IDE) – the Anaconda. The IDE usage was shown in a chronological sequence with accompanying visual outcomes. The use of plot libraries was discussed, and implemented in real life. One of the demonstration projects is the Zig-Zag plot. Studies were also done on sub-plotting, and how it is used in scientific visualizations, especially where there is necessity to generate variations of outputs originating from a singular dataset. The work also explores the use of pie charts for presentations. A real-life case of how this could be used to visualize the halls of a residential university was demonstrated, with each of the data components labelled in distinct colours. It is hoped that this work will serve as a foothold and useful guide to researchers and other practitioners involved in real life scientific visualization.
... To measure the productivity rate, mathematical and statistical analysis method are required to identify the failure factors and recommend for further improvement [3]. Tan et al. used the productivity mathematical model for a case study at a motorcycle production company which applied automated line in the final assembly line department [4]. Same goes to product quality rate that also can be measure by using mathematical and statistical analysis. ...
This paper aims to develop an improved general mathematical model by focusing on human factors variables that related to the product defect in the manufacturing production line. This is because many studies found that almost 40% of total defects resulted from the operator error and the defects are usually not obvious and neglected. The objective to have defect prediction mathematical model to satisfy as early quality indicator of the manufacturing flow production line and assist the quality control team in manufacturing industries. Thus, the human factor variables will be investigate thoroughly and final model can be used to predict product defect on the line to improve product quality. Product defects quantity are identified and analyzed to determine the potential predictors for developing the mathematical model. A case study is offered that illustrates in a spice packaging semi-automated production line the effect that complexity variables have on assembly quality. By using Minitab, Multiple Regression analysis is conducted to model the relationship between the input variables towards response variables. From the analysis, the predicted data showed reasonable correlation with the observed data improved with adjusted R-Sq from 2.6% to 7.9%. Hence, the regression equation obtain is selected to be the prediction mathematical model for defects based on human factor input variables.
... Productivity of longwall mining operations turns out to be a critical measure of performance of the emerging means of underground coal production [5]. There are several methods used across the industry to measure the productivity [6]. ...
... Productivity is measured as a key indicator to demonstrate the performance in manufacturing [60]. Since there exist several mathematical model studies for productivity in manufacturing system, one common equation of completely automated workplace or lines is produced and offered in Eq. 20 [61]: ...
A bi-objective flexible cell scheduling problem (CSP) under time-of-use (TOU) electricity tariffs in both deterministic and fuzzy environments are developed with the following objectives: (1) total cost of production system and (2) total delivery tardiness of jobs. To create a form of green and energy-conscious strategy, cost of produced emission and consumed power and some limitations on entire energy consumption, total manufactured emission, setup time, part defect (pert) percentage, system productivity, total number of tool slots, operations, and automated guided vehicles (AGVs) are respected. Besides, a self-adaptive two-phase subpopulation genetic algorithm (SATPSPGA) is taken to find a near-optimum solution of suggested bi-objective fuzzy mixed integer linear programming (FMILP) model. In view of the fact that no benchmark is existing in the literature, a self-adaptive non-dominated ranked genetic algorithm (SANRGA) and a non-dominated sorting genetic algorithm (NSGA-II) were employed to solve the model. To validate the result, a GAMS model of problem is utilized and compared with algorithm outcomes as well. Lastly, several numerical examples are offered to show the utility of the proposed methodology.
... Each level in the process is essential to achieve the optimum expected outcomes ("Study and Analysis the Wastage Reduction of Fluorescent Powder in CFL 23 W in Philips Pvt Ltd Mohali, Using Six Sigma Methodology," 2016). On the other hand, PACE Prioritization Matrix which was formed by Karen Martin Group, is a LEAN engineering tool established to explore the productivity parameters for increasing the production efficiency (Sin et al., 2014). ...
Productivity level is based on reliability impression which is the primary aspect of the automatic assembly line for continuous production. Productivity forecasting is a professional tool helping to enhance production system and attain the client petition by using precise model. Due to mechanisms complexity of assembly lines, analysis of failure factors contributes a significant role for investigating potential bounds that require analytical approach to compare the current and proposed model of productivity effects. The issues related to the production losses need additional space for improvement of the productivity model which may not present a close comparison between the current and proposed productivity rate. The main purpose of this paper is to develop a novel based productivity model that will predict alternatives for the availability of assembly line workspaces pertain to an automobile tire manufacturing plant. For investigating the potential bounds of the productivity losses, DMAIC and PACE techniques were used. It was revealed that the novel productivity model yielded better results of 3.358% errors showing its accuracy as compared to real productivity level at different workspaces.
... • Sin et al. (2014), com o título de "Parâmetros investigação de modelo matemático de pro- dutividade para a linha automatizada com disponibilidade pela metodologia DMAIC", em que os autores apresentam os parâmetros de investigação de perdas de produtivida-Implementação da metodologia Seis Sigma para melhoria de processos utilizando o ciclo DMAIC… rado um ciclo de desenvolvimento de projetos de melhoria e foi apresentado, originalmente, como parte do programa Seis Sigma (Gupta, 2005;Leaphart et al., 2012 O projeto se torna importante, pois a Quality X não está conseguindo atingir as me- tas de refugo previamente estabelecidas, acarre- tando atraso na entrega para a próxima célula de produção, podendo ocasionar parada, exces- so de produção entre estoque (para absolver a quantidade de peças refugadas no processo des- ta célula) e atraso na entrega para os clientes, além de estar gerando um déficit financeiro para a empresa, que totaliza aproximadamente 6 mil reais mensais. ...
Market globalization has brought deep changes to organizations, creating challenges, such as achieving cost reduction and improving levels of quality, in order to remain competitive. For this reason, increasingly, companies are seeking management methodologies that allow them to reduce costs and improve quality and customer satisfaction. Six Sigma is a highly quantitative management strategy whose purpose is to increase the performance and profitability of companies by improving the quality of products and processes and increasing customer satisfaction. This paper presents a case study of the application of Six Sigma in order to improve quality and reduce costs in a production line, using tools such as DMAIC, Ishikawa, and Pareto.
... Ocampo & Pavón (2012) performed a comparative analysis of the DMAIC methodology and the steps taken to develop a simulation model and propose a five-step methodology that incorporates both tools to analyze different scenarios. Chan et al. (2014) used the DMAIC methodology and PACE prioritization matrix (Priority, Action, Consider, and Eliminate) to improve and robust a mathematical model of productivity, they raise that productivity is one of the most important criteria in automated lines. ...
A dynamic model to analyze the complexity associated with the manufacturing systems and to improve the performance of the process through the Six Sigma philosophy is proposed. The research focuses on the implementation of the system dynamics tool to comply with each of the phases of the DMAIC methodology. In the first phase, define, the problem is articulated, collecting data, selecting the variables, and representing them in a mental map that helps build the dynamic hypothesis. In the second phase, measure, model is formulated, equations are developed, and Forrester diagram is developed to carry out the simulation. In the third phase, analyze, the simulation results are studied. For the fourth phase, improving, the model is validated through a sensitivity analysis. Finally, in control phase, operation policies are proposed. This paper presents the development of a dynamic model of the system of knitted textile production knitted developed; the implementation was done in a textile company in southern Guanajuato. The results show an improvement in the process performance by increasing the level of sigma allowing the validation of the proposed approach.
Napier grass fibre was utilized for the development of biocomposite
through nanocrystalline cellulose (NCC). NCC was generated by 64 wt% sulphuric
acid in the hydrolysis cycle with 60 min time reaction. Biocomposite in film form
has been prepared by mixing Poly (lactic acid) (PLA) and NCC using a method of
solvent casting. In manufacturing of biocomposite films, NCC with different composition (0, 3, and 6 wt%) was used. The result of XRD analysis displayed an increase
of crystallinity for PLA/NCC film compared to pure PLA film. However, PLA/NCC
film with 6 wt% content of NCC (PLA/NCC-6) exhibited the highest percentage of
crystallinity (69%). The chemical interaction of the structure between the NCC filler
and the polymer matrix was studied using FTIR which confirmed by the presence of
hydrogen bonding and the same trend of spectra was observed due to existence of
PLA. PLA/NCC-3 demonstrated the lowest water absorption (0.37%) compared to
pure PLA and PLA/NCC-6 film.
