El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The following study proposes a production management process model based on good practices and developed with process management tools for increasing crop productivity of pecan nuts using the Ica region in the district of Pachacutec as a study area. The study covers the proposed model’s diagnosis and development. The relation between these stages is the main function of improving pecan orchard productivity. The study showed that to increase pecan productivity from 1.09 (t/ha) to 2.21 (t/ha), and to determine raw material needs, tools and/or labor, a standardized process is needed for pecan production. The study’s main contribution is the development of a production management process through which farmers can order and control production by means of indicators. Furthermore, the study proposes that the developed process of pecan production currently applied by farmers should be supported by a mathematical model simulation.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / The reduction of waste is a constant concern for companies that form part of a supply chain. In industrial processors, these are related to logistics solutions, because the production process of the different products is highly automated. In the case of the Peruvian potato, this model is not applicable due to its irregular characteristics. In this context, this paper proposes an improvement in the process of elaboration of processed potatoes in order to reduce or eliminate waste in food sector companies. Identification tools are used for activities that do not generate value, such as the VSM, and other continuous improvement tools such as Kaizen and 5S, as well as a simulation model. In the validation, an 89% increase in the product yield, as well as a 72% efficiency increase, is obtained.

Currently, there is a large percentage of small and medium-sized enterprises (SMEs) in the Peruvian textile market that show economic loss because of the payment of penalties to customers, which are incurred owing to the delay in the delivery of order batches. This is due to poor production management and a lack of focus. The manufacturing sector is essential because of its high contribution to the country's gross domestic product. Currently, SMEs do not employ methodologies that help improve production and process management as they do not realize how important and necessary the methodologies are, in addition to how complex these may be. Therefore, this paper will propose a production management model designed for SMEs in this sector, based on Lean methodology where the objective is time reductions and production increases as well as exerting changes to the organizational culture. Thus, this model will help organizations to avoid incurring economic losses because of the payment of penalties for orders not delivered on time. To validate the present model, a time simulation was performed in the manufacturing area of a textile company. The result of this project was positive, since there was a 25% increase in productivity and a 20% reduction of takt time with respect to the initial data.

This research study seeks to identify and prioritize the causes of order fulfillment delays in a small wooden furniture manufacturing company. The authors propose a 5-phase Lean Optimization model to address and reduce this problem. Post-implementation results yielded a 54.87% reduction in material search and transportation times, a 32.86% reduction in travel times between stations, and a 19.81% increase in line efficiency. In addition, order fulfillment percentages increased from 12.5% to 60%.

Currently, small- and medium-sized enterprises face order fulfillment issues, thus generating reduced service levels. In addition, these companies are usually not aware of the importance of continuous improvement tools or of training staff as a mitigation strategy for this situation. Within this framework, the authors performed a literature review to compile production models through which downtimes could be reduced. The production model designed therefrom comprises Lean Manufacturing and work study tools within a Change Management approach. This design focuses on model implementation by small companies without requiring large investment, cutting-edge technology, or qualified personnel. Finally, an application case study was conducted in a small textile manufacturing company located at the Gamarra Fashion Center in Lima, Peru. The results that were reported revealed that late order fulfillment instances reduced by up to 18%, which had an impact on downtimes, unnecessary movements, and in-process inventory levels, thus increasing productivity by 85%.

This investigation proposes a lean model of production management for a small and micro enterprise (SME) dealing in packaging production in the auto parts sector, with the purpose of increasing efficiency in its production line. To this end, this model integrates study method tools and SMED, seeking to reduce waiting times and unnecessary operations, which have been identified as causing the problem on the basis of an initial diagnosis of the situation. Furthermore, to support and guarantee success in implementing these tools, John Kotter's Change Model is used. After two months of implementation, the results showed a 50% reduction in setup operation time and a 32% decrease in filing operation time, which are bottlenecks in the production process. Thus, with the new indicators, the line efficiency increased by 7% from the initial situation, thus showing improvement.

The focus of this research is to establish control and planning management in the sewing production process of lingerie clothing to better prepare companies for demand growth. The lack of improvement tools in this sector, the lack of staff training and a lack of quality culture has led to companies, especially MYPES, not being able to meet the established delivery times and non-fulfillment of orders with the customers, which represents 80% of dissatisfied orders due to the limited production capacity and non-productive time in the plant. This problem is due to limited production capacity, deficient production planning, and lack of materials. In order to solve this problem, industrial engineering tools were used. The application of these tools improved production from 79% to 95%.

En la actualidad, las industrias textiles presentan frecuentemente problemas en el área de producción, como los elevados tiempos de producción. Este es uno de los principales problemas que se presentan en este tipo de empresas, por la falta de organización de los procesos comprometiendo tanto la productividad como la competitividad de estas. Por ello, para la solución de este problema se propone la implementación de las herramientas del Lean Manufacturing y distribución de planta para reorganizar los procesos de producción, y a su vez, establecer métodos de trabajo adecuados, mediante el diseño de un modelo de optimización de tiempos en la producción, el cual consta en 2 fases enfocadas al proceso productivo y el personal. Como resultado de la implementación se obtendrá una reducción del tiempo de producción del 23.13% y 52.48%. del tiempo actual en el caso de edredones y sábanas, respectivamente. De la misma manera, se mejorará la productividad del operario, aumentando en 54.31% en el caso de edredones y 53.37% en sábanas. / At present, the textile industries frequently present problems in the production area, such as the long production times. This is one of the main problems that arise in this type of company, due to the lack of organization of the processes, compromising both their productivity and their competitiveness. Therefore, for the solution of this problem, the implementation of Lean Manufacturing tools and plant distribution is proposed to reorganize production processes, and in turn, establish appropriate work methods, by designing a time optimization model. in production, which consists of 2 phases focused on the production process and personnel. As a result of the implementation, a reduction in production time of 23.13% and 52.48% will be obtained. of the current time in the case of quilts and sheets, respectively. In the same way, the productivity of the operator will be improved, increasing by 54.31% in the case of quilts and 53.37% in sheets. / Trabajo de investigación

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The primary purpose of this thesis is to quantitatively analyze the production features of the Indonesian manufacturing sector. In particular, using concepts from traditional neoclassical theory of the firm, attention is focused on such aspects as returns to scale and the elasticity of factor substitution. Some empirical knowledge of these features of a production activity is important because of the crucial role they play in many theories of, for instance, growth and development economics, international trade and public economics. In order to measure returns to scale and elasticities of substitution, the approach adopted was that of production function analysis, using econometric techniques. Cross-sectional Indonesian data for 1983 were fitted to both Cobb-Douglas and CES-type production functions, and the unit of observation is the establishment. Ordinary least squares method was applied in estimating the regression models. Chapter One is an introductory exposition. It describes the aim and the purpose of the study, while Chapter Two gives a general description of the manufacturing sector as a component of the national economy. Chapters Three and Four are the main substance of the thesis. In Chapter Three, a theoretical discussion of production functions and common problems usually encountered on the estimation of neoclassical aggregate production functions are given. The chapter is concluded with the discussion and definitions of the data used for the study. Two specifications for the tests of returns to scale and one specification for the tests of elasticity of substitution were formulated in chapter four. And 20 industries were tested for each specification. The results indicate that the majority of these industries show constant returns to scale. Moreover, most of them show elasticity of factor substitution greater than one. / M.A.