Person:
Llivisaca Villazhañay, Juan Carlos

Birth Date

1987-03-05

ORCID

0000-0003-2154-3277

Scopus Author ID

57212004129

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Facultad de Ciencias Químicas, Cuenca, Ecuador
Universidad Politécnica Estatal del Carchi, Tulcán, Ecuador
Universidad de Valladolid, Valladolid, España

País

Ecuador

Organizational Units

Organizational Unit

Facultad de Ciencias Químicas

Fundada en 1955 como la Escuela de Química Industrial, la facultad ha sido un pilar fundamental en la formación de profesionales altamente capacitados, comprometidos con el desarrollo de la ciencia, la educación y el bienestar social. La Facultad de Ciencias Químicas pone a consideración su trabajo académico, investigativo y de vinculación con la sociedad, desarrollado a través de la práctica de una docencia de calidad, investigación e innovación en su área de estudio. Desde su oficio de conocimiento se permite contribuir a la sociedad con cuatro carreras: Bioquímica y Farmacia, Ingeniería Química, Ingeniería Ambiental e Ingeniería Industrial. Su carta de presentación en la Academia, la coloca como una dependencia dinámica, donde confluye la solidez de una trayectoria de más de sesenta años. Aquí se trabaja en una continua formación de pregrado y posgrado de la más alta calidad, mediante la mejora continua con la innovación y a la vanguardia de las ciencias químicas.

Job Title

Profesor (T)
Coordinador de Investigación del grupo IMAGINE

Last Name

Llivisaca Villazhañay

First Name

Juan Carlos

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Now showing 1 - 10 of 13

Customer Segmentation in Food Retail Sector: An Approach from Customer Behavior and Product Association Rules
(Springer, 2022) Llivisaca Villazhañay, Juan Carlos; Aviles Gonzalez, Jonnatan Fernando; Llivisaca Villazhañay, Juan Carlos
In competitive markets, customer segmentation improves customer loyalty and business performance, but in practice, these analyses are carried out using simple relationships in dashboard, or Microsoft Excel’ sheets, which do not show customer behavior. Data segmentation in the era of big data has changed this paradigm with some techniques that try to decrease bias. In this research, four segmentation techniques are tested with a large set of data from a retail store. CLARA (Clustering Large Applications Algorithm) and Random Forest algorithms both were the best. Through the RFM (Recency, Frequency, Monetary) approach, eight customer segments were found, where Champions customers spend more money and return frequently to the retail store. In addition, each segment of customer buys following a model, this was demonstrated with the a priori algorithm. Finally, some strategies are given into which products should go together and how to distribute them so that customers can find them, as well as the best-selling products.
Optimization of motorcycle assembly processes based on lean manufacturing tools
(Springer, 2020) Quezada Cazorla, Jonnathan David; Sigüenza Guzmán, Lorena Catalina; Llivisaca Villazhañay, Juan Carlos
Global competition and economic dynamism force the assembly industry to look for productive philosophies of improvement, optimizing processes, and resources. The challenge in the optimization process involves finding tools that will grant an optimal process. This article proposes a process optimization through the application of Lean Manufacturing tools, with the necessary guidelines analyzed and verified by computational simulation in a motorcycle assembler. Firstly, applying a plant distribution, together with the change of productive system, allowed the reduction of distances, elimination of unnecessary movements, and reprocessing. Then, Pull System reduced the stock of both the product in process and the final product in the warehouse, avoiding the generation of future waste and expenses due to overproduction. Finally, the use of the 5S tool entailed maintaining order and cleanliness inside the plant to facilitate the management of internal resources. In the study reported, an average reduction of 40% in assembly time and an average increase in production of 30% of all motorcycle models that were part of the study are achieved.
Key performance indicators for the supply chain in small and medium sized enterprises based on balance score card
(2020) Llivisaca Villazhañay, Juan Carlos; Jadán Avilés, Diana Carolina; Guamán Guachichullca, Noé Rodrigo; Arcentales Carrión, Rodrigo Nicanor; Peña Ortega, Mario Patricio; Sigüenza Guzmán, Lorena Catalina
A supply chain is a network of interaction between different actors, and indi-cators govern its behavior. The current research deals with the analysis and ranking of critical indicators for the supply chain in small and medium-sized enterprises (SMEs). To this end, firstly, a systematic review of supply chain management indicators for SMEs was carried out. Using data sources such as Scopus, ProQuest, and Google Scholar, 189 metrics were selected. Then, through practical and methodological filters, this number was reduced to 149. To organize these indicators, both models, the Balanced Scorecard (BSC) and the Supply Chain Operations Reference (SCOR-model), were used to connect company strategies to their performance. Secondly, these measures formed part of a questionnaire answered by 30 SME experts. From their responses, critical indicators were evaluated through Principal Component Analysis (PCA), resulting in 50 key indicators. Finally, these indicators were ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). For SCM in SMEs, findings indicate that the primary key perfor-mance indicators (KPIs) are cash flow, satisfaction rate, inventory rotation, and exchange of information through the supply chain.
Optimization models used in the textile sector: a systematic review
(Springer Science and Business Media Deutschland GmbH, 2022) Llivisaca Villazhañay, Juan Carlos; Veintimilla Reyes, Jaime Eduardo; Sigüenza Guzmán, Lorena Catalina; Torres Torres, Christian Marcelo; Toledo Illescas, María Belén; Peña Ortega, Mario Patricio
In recent years, several works have been published dedicated to obtaining optimization models. Many of them have been applied in the textile sector because they are part of the economic development areas of a country. This article’s main objective is to review the literature published on optimization models and understand what methods their authors used to solve the optimization problems in the textile sector. A systematic methodology was applied to select research questions, digital databases, and search terms to utilize practical and methodological filters later to carry out this systematic review. This procedure allowed performing a review and synthesis of the results obtained on the optimization models. It was found that the models resulting from the systematic review vary depending on the areas to be optimized. The most frequent applications were logistics and production, followed by cost minimization. They were optimized mainly with linear programming, integer programming, Markov chains, genetic algorithms, and multi-objective programming
An overview of optimization models and technological trends of logistics in the retail sector
(Springer Science and Business Media Deutschland GmbH, 2022) Peña Ortega, Mario Patricio; Jadán Avilés, Diana Carolina; Sigüenza Guzmán, Lorena Catalina; Guamán Guachichullca, Noé Rodrigo; Arcentales Carrión, Rodrigo Nicanor; Llivisaca Villazhañay, Juan Carlos
Recently, the e-commerce market has grown rapidly. For example, e-commerce generated sales of USD 504 billion in the US from January 1, 2020, to July 1, 2020, representing an increase of 11.58% over the same period in 2019. This growth has forced the retail industry has had to adopt strategies to become more efficient. About 40% of many companies ‘available time is devoted to logistics. Because these activities are consuming a disproportionate share of many companies’ time, logistics is a prime topic of interest. In this context, this study aims to present an overview of optimization models and technological trends in logistics in the retail sector. Findings show that retail logistics has focused on reducing costs, time usage, and inventories while increasing transport capacity. Optimization in logistics has focused on using mathematical algorithms such as genetic algorithms with different variants, and simulation has supported testing optimization proposals. Finally, big data, omnichannel, and e-commerce continue to grow, especially in the retail sector where it has grown considerably
Assessment of supply chain performance in an assembly company: evaluation of evolutionary algorithms
(Springer, Singapore, 2020) Orellana Ordoñez, Josselin Jimena; Peña Ortega, Mario Patricio; Llivisaca Villazhañay, Juan Carlos
In current globalized markets, companies no longer compete with each other. They now compete with the supply chains (SC) to which they belong. SC optimization allows efficient and effective management of resources. In many cases, optimization goals can conflict with one another. Therefore, the purpose of this work was to evaluate SC performance by comparing three optimization algorithms in a case study with multiple objectives. Two objectives are maximizing profit and maximizing the level of customer service. Also, the modeled problem considers multiple products and periods for two security inventory scenarios (maximum and minimum inventory levels). Evolutionary algorithms were compared: NSGA-II, MOPSO, and MOMA. The NSGA-II algorithm obtained the best result. With a minimum inventory level, NSGA-II presented 97.87% service level and the best benefit. Results show the importance of SC management and its optimization as well as some relevant variables to be considered.
Technologies applied to solve facility layout problems with resilience – a systematic review
(Springer International Publishing, 2022) Sigüenza Guzmán, Lorena Catalina; Naranjo Ríos, Jonnathan Israel; Vázquez Mendoza, Jorge Alberto; Llivisaca Villazhañay, Juan Carlos; Ortiz Guerrero, Daysi Margarita
In the industry, the need to optimize daily tasks became mainly a requirement to stay competitive. The Facility Layout Problem (FLP) arises from this need and is the most used technique to improved manufacturing processes. Over the years, the distribution of the different facilities became more complex and more susceptible to interventions in their usual workflow. Hence, FLPs emerged to solve these interventions. This capacity to solve various problems is known as resilience. By searching the literature for information on technologies used to solve FLP, many software solutions can be obtained. Still, none of them manage resilience as a factor in the solution. They have also not been compiled in an analysis to determine the most modern options for existing solutions. The current study reviews the most widely used software tools that solve FLP and how these studies view resilience. A systematic literature review was applied to select relevant studies from 2015–2021. This work allowed analyzing a final sample of 133 articles obtained in two different search strings. As a result, this study identified two manners to solve FLP with software tools: using already developed tools and developing an own tool. In the former, three proprietary software were identified: MATLAB, CPLEX, and LINGO. When developing their software tool, the technology used varies significantly between studies. They use very different language programming, depending on the researcher’s domain. Furthermore, the results do not find any case in which some resilience factor was part of the solution obtained.
Internal logistics optimization based on a multi-objective linear model for micro, small, and medium textile enterprises
(Springer International Publishing, 2022) Llivisaca Villazhañay, Juan Carlos; Peña Ortega, Mario Patricio; Sigüenza Guzmán, Lorena Catalina; Veintimilla Reyes, Jaime Eduardo; Torres Torres, Christian Marcelo; Toledo Illescas, María Belén
Daily, textile companies seek to increase production levels through available resources and improve their profit projections over time. Therefore, it is essential to manage the products to be manufactured based on their raw materials resources and time availability. This work proposes improving decision-making in textile production planning by applying a multi-objective linear optimization model to internal logistics within micro, small, and medium-sized enterprises (MSMEs) of the Ecuadorian textile sector. The application of this optimization model results in a balanced production plan between the objectives related to profit maximization and the use of the time available for production. This article includes the description of the studied case, the definition of the optimization model executed by using the Gurobi solver, the results of the application of the optimization model with the data provided by a case study, and the discussion of the results through a sensitivity analysis.
Relevant factors in the inventory record inaccuracy for retail companies: a study in food retail industry
(Springer Science and Business Media Deutschland GmbH, 2022) Espinoza Aguirre, Jorge Andrés; Jadán Avilés, Diana Carolina; Peña Ortega, Mario Patricio; Llivisaca Villazhañay, Juan Carlos
Retail companies are an essential industry for economic development in every country. In these organizations, at least 60% of the assets correspond to inventory. Therefore, inventory record inaccuracy (IRI) is a problem among these companies. IRI is the gap generated between physical audits and system records, which affects the retailer by changing their book value, increasing economic losses, and providing poor customer service. This study aims to identify the factors that cause IRI in retail companies and, using a mathematical model, works to help retailers minimize the gap between registers. As a consequence, retailers can reduce potential losses in the company. Two mathematical models are proposed for each of the dependent variables: IRI and difference between records. The independent variables considered are quantity of sale of an item, cost, physical audit period, variety of products, product returns, sale price, and quantity sold. This work concludes by comparing both models, highlighting the most influential variables
Blockchain and its potential applications in food supply chain management in Ecuador
(Springer, 2020) Peña Ortega, Mario Patricio; Llivisaca Villazhañay, Juan Carlos; Sigüenza Guzmán, Lorena Catalina
In recent years, attention has been directed to the problem of food loss and waste. On the one hand, there is an increasing demand for higher quality fresh produce and products. On the other hand, studies suggest that at least one-third of food production is lost along its supply chain. The most crucial part is constituted by suppliers-retailers-consumers, since it presents the highest percentages of loss or waste. Several works in the literature suggest that the exchange of information is one of the most important means to reduce waste. Shared information can improve decisions regarding the quantity in supplier’s orders and vendor’s inventory allocation among retailers. Based on these needs, the Blockchain technology, developed in recent years to generate secure transactions on different sectors, has the characteristics of decentralization, information security, and reliability. If this technology can be applied as an underlying basis of a supply chain, it could improve exchanges of information and products among all parts of the system. In this context, the current article presents a systematic review on Blockchain in food supply chain management (FSCM) in Ecuador, its main contributions, and potential benefits. Findings indicate that Blockchain in FSCM is a recent research area whose importance is rapidly growing. However, little is known about Ecuadorian studies applying Blockchain. Additionally, no studies have reported the combination of Blockchain and Internet of Things technologies, one of the most prominent and complementary applications of Blockchain.