8 research outputs found

    Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

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    In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method

    A multi-stage stochastic programming approach in master production scheduling

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    Master Production Schedules (MPS) are widely used in industry, especially within Enterprise Resource Planning (ERP) software. The classical approach for generating MPS assumes infinite capacity, fixed processing times, and a single scenario for demand forecasts. In this paper, we question these assumptions and consider a problem with finite capacity, controllable processing times, and several demand scenarios instead of just one. We use a multi-stage stochastic programming approach in order to come up with the maximum expected profit given the demand scenarios. Controllable processing times enlarge the solution space so that the limited capacity of production resources are utilized more effectively. We propose an effective formulation that enables an extensive computational study. Our computational results clearly indicate that instead of relying on relatively simple heuristic methods, multi-stage stochastic programming can be used effectively to solve MPS problems, and that controllability increases the performance of multi-stage solutions

    Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model

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    [EN] Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.This research was initiated within the framework of the project funded by the Ministerio de Economía y Competitividad [Ref. DPI2011-23597] entitled ‘Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity’ (PLANGES-FHP) already finished. After, the project leading to this application has received funding from the European Union’s research and innovation programme under the H2020 Marie Skłodowska-Curie Actions with the grant agreement No 691249, Project entitled ’Enhancing and implementing Knowledge based ICT solutions within high Riskand Uncertain Conditions for Agriculture Production Systems’ (RUC-APS).Mundi, I.; Alemany Díaz, MDM.; Poler, R.; Fuertes-Miquel, VS. (2019). 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    A review of discrete-time optimization models for tactical production planning

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    This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

    Experimentell rangordning av antändligheten hos kläder som används av riskgrupper

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    The purpose of this report is to find out which composition of fibres in clothes are the easiest to ignite when exposed to a smouldering fire (i.e. a cigarette). The end result of this report were several rankings concerning the ignitability of sweaters made of polar fleece, WCT-overalls, knitted cardigans (sweaters), dressing gowns (bathrobes) and sweatpants. Several conclusions could be made and one of them is that 100 % viscose and 100 % cotton should be avoided because of their propensity to ignite. The second conclusion was that mixtures of cotton/polyester and cotton/viscose should be avoided. Even thou cotton/polyester ignited fewer times it had an ignition time that were significantly shorter which makes it more dangerous. If a decision should be made a blend of cotton/viscose is preferred before cotton/polyester. A content of at least 5 % elastan (also called spandex and lycra) in cotton/elastan mixtures and cotton/polyester/elastan mixtures should be sought since these didn’t ignite. In general 100% polyester together with 100 % wool and 100 % silk were among the least dangerous materials since they did not ignite. A low weight (i.e. g/m2) of 100% cotton should be sought since the afterglow tend to decrease when the weight decreases

    Use of electronic supply chain management in overcoming uncertainty constraints: South African textile industry.

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    Masters Degree. University of KwaZulu-Natal, Durban.Background: The impact of the internet and other technological advancements of the 21st century have improved business capability through speeding up global supply chains, driving innovation and widening the geographic scope of purchasing activities. However, such enhancements have detrimentally affected labour-intensive industries including the South African clothing and textile industry which has faced multiple job losses. Problem: Economies of scale, enhanced technologies and lower labour costs have put international competitors at an advantage. Increased import tariffs have had a marginal impact. The impacts of Covid-19 have negatively impacted the spending power and confidence of consumers, causing demand uncertainty. Purpose: It was proposed that the alignment of industry operators with the electronic supply chain management (eSCM) activities of worldwide industry leaders may provide respite to operators in the sector amidst uncertainty. The purpose of this study was to study the truth of this proposal. Methodology: This proposal was tested in three stages. Firstly, a review of previous literature set out to explain the current uncertainties faced in the industry before providing an understanding what the possible forms of eSCM implementation are. Highlighted technologies included ERP, e-marketplaces and automation. Thereafter, the study shifted toward qualitative primary research. First, a case study was conducted to the perspective of a selected company which had implemented eSCM practices. Comprising of open-ended questions posed to managers at the company, the case study studied the uncertainties it faces and eSCM activities used to thrive amidst these uncertainties. The second part of the primary research involved face-to-face interviews with industry experts on the generalisability of the case study. Results: It was evident that eSCM technologies positively impacted business’ aims for efficiency, flexibility and improved communication to manage amidst uncertainty. However, participants cite that inadequate commitment often rendered technology futile. Participants cited that gradual implementation would be fruitful. Contribution: ESCM adoption has been studied in numerous industries globally. Not much literature focuses on local eSCM adoption, with previous research focusing on customer-facing organisations in the sector. This study included multiple tiers in the supply chain, with the company performing both retail and manufacturing activities. Implications: SMME’s nationwide should adopt needs-based eSCM practices, whether they are customer-facing or are involved in the transformation of clothing and textile goods

    Mejora de tiempos de entrega en un flow shop híbrido flexible usando técnicas inteligentes. Aplicación en la industria de tejidos técnicos

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    Se busca aportar herramientas útiles para la programación de producción en la industria de tejidos técnicos. Se parte de las condiciones actuales de la programación de producción en este tipo de industria y de los antecedentes en la literatura científica sobre modelos aplicables a estos entornos. Se propone un modelo de solución por técnicas inteligentes a la problemática de la secuenciación y asignación de tareas en los entornos flow shop híbrido flexible considerando situaciones como: paralelismo entre máquinas no relacionadas, tiempos de montaje dependientes de la secuencia, entrada dinámica de trabajos, restricción de elegibilidad, maleabilidad y lotes de transferencia variables entre etapas. De allí se construye la propuesta de solución que involucra simultáneamente todas las condiciones de entorno real mencionadas y aplica un algoritmo genético modificado de acuerdo a las características del problema. Se concluye que el modelado considerando condiciones realistas es posible, que los algoritmos genéticos son una opción práctica para entornos reales y que las empresas pueden obtener mejoras en su capacidad de respuesta con este tipo de solucionesAbstract : It seeks to provide useful tools for production scheduling in the technical textiles industry. It begins in the current conditions of production scheduling in this type of industry and the background in scientific literature, applicable to these environments models. The mathematical model to solve the problem of sequencing and assigning jobs in Flexible hybrid flow shop environments is developed considering: unrelated parallel machines, sequence dependent setup time, dynamic entry of jobs, availability constrain, malleability and variable transfer batches between stages. The solution proposal is build including all actual environment features considered together and applying a modified genetic algorithm modeled according to the problem. It is concluded that the model of scheduling problems considering realistic conditions is possible, that genetic algorithms are a practical option for real environments, and that companies can achieve improvements in their responsiveness with this kind of solutionsDoctorad

    MRP IV: Planificación de requerimientos de materiales cuarta generación. Integración de la planificación de la producción y del transporte de aprovisionamiento

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    Tesis por compendioEl sistema de planificación de requerimientos de materiales o MRP (Material Requirement Planning), desarrollado por Orlicky en 1975, sigue siendo en nuestros días y, a pesar de sus deficiencias identificadas, el sistema de planificación de la producción más utilizado por las empresas industriales. Las evoluciones del MRP se vieron reflejadas en el sistema MRPII (Manufacturing Resource Planning), que considera restricciones de capacidad productiva, MRPIII (Money Resource Planning), que introduce la función de finanzas; y la evolución comercial del mismo en el ERP (Enterprise Resource Planning), que incorpora modularmente todas las funciones de la empresa en un único sistema de decisión, cuyo núcleo central es el MRP. Los desarrollos posteriores de los sistemas ERP han incorporado las nuevas tecnologías de la información y comunicaciones. Asimismo, éstos se han adaptado al contexto económico actual caracterizado por la globalización de los negocios y la deslocalización de los proveedores desarrollando otras funciones como la gestión de la cadena de suministro o del transporte, entre otros. Por otro lado, existen muchos trabajos en la literatura académica que han intentado resolver algunas de las debilidades del MRP tales como la optimización de los resultados, la consideración de la incertidumbre en determinados parámetros, el inflado de los tiempos de entrega, etc. Sin embargo, tanto en el ámbito comercial como en el científico, el MRP y sus variantes se centran en el requerimiento de los materiales y en la planificación de las capacidades de producción, lo que es su desventaja principal en aquellas cadenas de suministro donde existe una gran deslocalización de los proveedores de materias primas y componentes. En estos entornos, la planificación del transporte adquiere un protagonismo fundamental, puesto que los elevados costes y las restricciones logísticas suelen hacer subóptimos e incluso infactibles los planes de producción propuestos, siendo la re-planificación manual una práctica habitual en las empresas. Esta tesis doctoral propone un modelo denominado MRPIV, que considera de forma integrada las decisiones de la planificación de materiales, capacidades de recursos de producción y el transporte, con las restricciones propias de este último, tales como diferentes modos de recogida (milk-run, camión completo, rutas) en la cadena de suministro con el objetivo de evitar la suboptimización de estos planes que en la actualidad se generan usualmente de forma secuencial e independiente. El modelo propuesto se ha validado en una cadena de suministro del sector del automóvil confirmando la reducción de costes totales y una planificación más eficiente del transporte de los camiones necesarios para efectuar el aprovisionamiento.Díaz-Madroñero Boluda, FM. (2015). MRP IV: Planificación de requerimientos de materiales cuarta generación. Integración de la planificación de la producción y del transporte de aprovisionamiento [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48524TESISCompendi
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