International Journal of Production Management and Engineering - Vol 11, No 2 (2023)
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Artículos
- Principles of cellular manufacturing/engineering/management: case studies and explications
- Chaos synchronization for a class of uncertain chaotic supply chain and its control by ANFIS
- Fulfillment costs in online grocery retailing: comparing retail store and warehouse strategies
- Two stages of halal food distribution model for perishable food products
- BASA: An improved hybrid bees algorithm for the single machine scheduling with early/tardy jobs
- An industry maturity model for implementing Machine Learning operations in manufacturing
- The value chain approach in red biotechnology companies from a bibliometric perspective
- Green lean method to identify ecological waste in a nectar factory
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- PublicationGreen lean method to identify ecological waste in a nectar factory(Universitat Politècnica de València, 2023-07-31) Bancovich Erquínigo, Andrei; Ortiz Porras, Jorge; Quintana Saavedra, Harold; Crispin Chamorro, Paola; Manrique Alva, Rosiand; Vilca Carhuapuma, Pedro[EN] Nowadays, the waste of resources has become one of the biggest problems for industries, due to the serious environmental, social and economic consequences it generates. Therefore, to ensure a production based on sustainable processes, it s essential to have a responsible management of resources, being the first step one of the most important ones, the identification. Thus, the present research work aims to develop and implement a method based on the integration of Green and Lean methodologies to systematically identify ecological waste, taking as a case study a nectar factory in Lima - Peru. Through the implementation of tools such as Environmental Value Stream Mapping, Process Mapping or Failure Mode and Effects Analysis, it was found that the company generated a waste of 1584 litres of water and 38.5 kg of conditioned fruit every month. The identification of green waste is vital, as it is the first link in a long chain that contributes directly to improving the company's efficiency, profitability and reputation, as well as protecting the environment and promoting sustainable development.
- PublicationThe value chain approach in red biotechnology companies from a bibliometric perspective(Universitat Politècnica de València, 2023-07-31) Oramas Santos, Onailis; Canós Darós, Lourdes; Babiloni, Eugenia; Departamento de Organización de Empresas; Facultad de Administración y Dirección de Empresas; Grupo de Investigación en Reingeniería, Organización, trabajo en Grupo y Logística Empresarial - ROGLE[EN] This paper analyzes the value chain approach in the red biotechnology sector from a bibliometric perspective, using Scopus and Web of Science databases from 2011 to 2021. As a result, 82 documents that cover this topic are analyzed with VOSviewer and R studio. The main findings show that scientific interest increases with a positive publication trend during the considered time period. However, there are no authorship networks in both database. Furthermore, the main reason to use the value chain approach in the red biotech sector is that it highlights the government s implication on the industry, given its social impact. As a research gap, we recommend to study the effects of Industry 4.0 on the red biotech value chain approach.
- PublicationAn industry maturity model for implementing Machine Learning operations in manufacturing(Universitat Politècnica de València, 2023-07-31) Mateo Casalí, Miguel Ángel; Fraile Gil, Francisco; Boza García, Andrés; Nazarenko, Artem; Departamento de Organización de Empresas; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Técnica Superior de Ingeniería Informática; European Commission[EN] The next evolutionary technological step in the industry presumes the automation of the elements found within a factory, which can be accomplished through the extensive introduction of automatons, computers and Internet of Things (IoT) components. All this seeks to streamline, improve, and increase production at the lowest possible cost and avoid any failure in the creation of the product, following a strategy called Zero Defect Manufacturing . Machine Learning Operations (MLOps) provide a ML-based solution to this challenge, promoting the automation of all product-relevant steps, from development to deployment. When integrating different machine learning models within manufacturing operations, it is necessary to understand what functionality is needed and what is expected. This article presents a maturity model that can help companies identify and map their current level of implementation of machine learning models.
- PublicationBASA: An improved hybrid bees algorithm for the single machine scheduling with early/tardy jobs(Universitat Politècnica de València, 2023-07-31) Abdessemed, Ahmed Adnane; Mouss, Leila Hayet; Benaggoune, Khaled[EN] In this paper, we present a novel hybrid meta-heuristic by enhancing the Basic Bees Algorithm through the integration of a local search method namely Simulated Annealing and Variable Neighbourhood Search like algorithm. The resulted hybrid bees algorithm (BASA) is used to solve the Single Machine Scheduling Problem with Early/Tardy jobs, where the generated outcomes are compared against the Basic Bees Algorithm (BA), and against some stat-of-the-art meta-heuristics. Computational results reveal that our proposed framework outperforms the Basic Bees Algorithm, and demonstrates a competitive performance compared with some algorithms extracted from the literature.
- PublicationTwo stages of halal food distribution model for perishable food products(Universitat Politècnica de València, 2023-07-31) Dwi Agustina Kurniawati; Rochman, Muhammad Arief[EN] Two stages of halal food distribution model for perishable food products are a mixed integer linear program (MILP) model proposed to solve the distribution problem of halal food, especially for perishable food products. The model can simultaneously minimize overstock, shortage, transportation, and deterioration costs. The model is developed into two stages. The first stage is the location-allocation model to determine the halal cluster and the number of suppliers in each cluster. The second stage is the vehicle routing model to determine the routing at each cluster. Numerical experiments are done using CPLEX Solver and the proposed model is applied to solve a real case of halal meat distribution in Yogyakarta. The results show that the proposed model can be used as a decision tool for supply chain and distribution managers to determine the strategy for distributing halal food products with the least total logistics cost for daily application.