Advanced methods and models in uncertainty for the order promising process in supply chain characterized by the lack of homogeneity in product

Tesis por compendioThe Lack of Homogeneity in the Product (LHP) appears in productive processes with raw materials, which directly stem from nature and/or production processes with operations that confer heterogeneity to the characteristics of the outputs obtained, even when the inputs used are homogeneous. LHP appears in different sectors such as ceramic tile, horticulture, marble, snacks, among others. LHP becomes a managerial problem when customers require to be served with homogeneous product. Supply chains responsible to provide homogeneous product face the need to include classification activities in their productive processes to obtain sub-lots of homogeneous product. Due to the inherent LHP uncertainty, these homogeneous sub-lots will not be known until the product have been produced and classified. An improper management of the LHP can have a very negative impact on the customers' satisfaction due to inconsistencies in the answer to their requirements and also on the Supply Chain's efficiency. The Order Promising Process (OPP) appears as a key element for properly managing the LHP in order to ensure the matching of uncertain homogeneous supply with customer order proposals. The OPP refers to the set of business activities that are triggered to provide a response to the orders from customers. These activities are related to the acceptance/rejection decision, and to set delivery dates. For supply chains affected by the LHP, the OPP must consider the homogeneity as another requirement in the answer to the orders. Besides, due to the LHP inherent uncertainty, discrepancies between the real and planned homogeneous quantities might provoke that previously committed orders cannot be served. The Shortage Planning (SP) process intends to find alternatives in order to minimise the negative impact on customers and the supply chain. Considering LHP in the OPP brings a set of new challenging features to be addressed. The conventional approach of assuming homogeneity in the product for the master production schedule (MPS) and the quantities Available-To-Promise (ATP) derived from it is no longer adequate. Instead, both the MPS and ATP should be handled in terms of homogeneous sub-lots. Since the exact quantity of homogeneous product from the planned lots in the MPS is not exactly known until the classification activities have been performed, the ATP also inherits this uncertainty, bringing a new level of complexity. Non-homogeneous product cannot be accumulated in order to fulfil future incoming orders. Even more, if the product handled is perishable, the homogeneity management becomes considerably more complex. This is because the state of the product is dynamic with time and related variables to it, like quality, price, etc., could change with time. This situation could bring unexpected wasting costs apart from the shortages already mentioned. The perishability factor is itself another source of uncertainty associated to the LHP. This dissertation proposes a conceptual framework and different mathematical programming models and tools, in both deterministic and uncertainty environments, in order to support the OPP and SP under LHP's effect. The aim is to provide a reliable commitment with customer orders looking for a high service level not just in the due date and quantity but also in the homogeneity requirements. The modelling of the characteristics inherent to LHP under deterministic context constitutes itself one of the main contribution of this dissertation. Another novelty consists in the inclusion of uncertainty in the definition of homogeneous sub-lots, their quantities and their dynamic state and value. The uncertainty modelling approach proposed is mainly based on the application of fuzzy set theory and possibility theory. The proposed mathematical models and tools have been validated in real cases of SC, specifically in the ceramic tile sector for non perishables, and in the fruit sector for perishables. The results show a ...La Falta de Homogeneidad en el Producto (LHP, por sus siglas del inglés ``Lack of Homogeneity in the Product'') aparece en procesos productivos con materias primas que derivan directamente de la naturaleza y/o procesos de producción con operaciones que confieren heterogeneidad a las características de los productos obtenidos, incluso cuando los insumos utilizados son homogéneos. La LHP aparece en diferentes sectores como la cerámica, horticultura, mármol, snacks, entre otros. Se convierte en un problema gerencial cuando los clientes requieren homogeneidad en el producto y las cadenas de suministro enfrentan la necesidad de incluir actividades de clasificación en sus procesos productivos para obtener sub-lotes de producto homogéneo. Debido a la incertidumbre inherente a la LHP, los sub-lotes homogéneos y su cantidad no serán conocidos hasta que el producto haya sido producido y clasificado. Una gestión inadecuada de la LHP puede tener un impacto muy negativo en la satisfacción de los clientes debido a inconsistencias en la respuesta a sus requerimientos y también en la eficacia de la Cadena de Suministro. El Proceso de Comprometer de Pedido (OPP, por sus siglas del inglés ``Order Promising Process'') aparece como un elemento clave para gestionar adecuadamente la LHP, con el fin de asegurar la coincidencia entre el suministro incierto de producto homogéneo y las propuestas de pedido del cliente. El OPP se refiere al conjunto de actividades empresariales realizadas para proporcionar una respuesta a las órdenes de los clientes. Estas actividades están relacionadas con las decisiones de aceptación/rechazo, y establecimiento de fechas de entrega para las órdenes del cliente. En las cadenas de suministro afectadas por la LHP, el OPP debe considerar la homogeneidad como otro requisito adicional en la respuesta a los pedidos. Además, debido a la incertidumbre intrínseca de la LHP, las discrepancias entre las cantidades homogéneas reales y planificadas podrían provocar que las órdenes comprometidas anteriormente no puedan ser completadas debido a la escasez de producto. El proceso de planificación de la escasez (SP, por sus siglas del inglés "Shortage Planning") se encarga de encontrar alternativas para minimizar este impacto negativo en los clientes y la cadena de suministro. Considerar la LHP dentro del OPP implica un conjunto nuevo de características desafiantes que deben ser abordadas. El enfoque convencional de asumir la homogeneidad en el producto para el programa maestro de producción (MPS, por sus siglas del inglés "Master Production Schedule") y las cantidades disponibles a comprometer (ATP, por sus siglas del inglés "Available-To-Promise") derivadas de él, no es adecuado. En cambio, tanto el MPS como el ATP deben manejarse en términos de sub-lotes homogéneos. Dado que la cantidad exacta de producto homogéneo de los lotes previstos en el MPS no se sabe exactamente hasta que se han realizado las actividades de clasificación, el ATP también hereda esta incertidumbre, trayendo un nuevo nivel de complejidad. El producto no homogéneo no se puede acumular para satisfacer futuras órdenes entrantes. Más aún, si el producto manipulado es perecedero, el manejo de la homogeneidad se vuelve mucho más complejo. Esto se debe a que el estado del producto es dinámico en el tiempo, y variables relacionadas como calidad, precio, etc., podrían también cambiar con el tiempo. Esta situación puede provocar costos inesperados de desperdicio aparte de la escasez ya mencionada. El factor de perecedero es en sí mismo otra fuente de incertidumbre asociada a la LHP. Esta disertación propone un marco conceptual y diferentes modelos y herramientas de programación matemática, tanto en entornos deterministas como de incertidumbre, para apoyar al OPP y SP considerando el efecto de LHP. El objetivo es proporcionar un compromiso fiable con los pedidos de los clientes en busca de un alto nivel de servicio no sLa Falta d'Homogeneïtat en el Producte (LHP, per les seues sigles de l'anglés ''Lack of Homogeneity in the Product'') apareix en processos productius amb matèries primes que deriven directament de la natura i/o processos de producció amb operacions que conferixen heterogeneïtat a les característiques dels productes obtinguts, fins i tot quan les entrades utilitzades són homogènies . La LHP apareix en diferents sectors com la ceràmica, horticultura, marbre, snacks, entre altres. Es convertix en un problema gerencial quan els clients requereixen homogeneïtat en el producte i les cadenes de subministrament enfronten la necessitat d'incloure activitats de classificació en els seus processos productius per a obtindre sublots de producte homogeni. A causa de la incertesa inherent a la LHP, els sublots homogenis i la seua quantitat no seran coneguts fins que el producte haja sigut produït i classificat. Una gestió inadequada de la LHP pot tindre un impacte molt negatiu en la satisfacció dels clients degut a inconsistències en la resposta als seus requeriments i també en l'eficàcia de la Cadena de Subministrament. El Procés de Comprometre Comandes (OPP, per les seues sigles de l'anglés ''Order Promising Process'') apareix com un element clau per a gestionar adequadament la LHP, a fi d'assegurar la coincidència entre el subministrament incert de producte homogeni i les propostes de comanda del client. L'OPP es refereix al conjunt d'activitats empresarials realitzades per a proporcionar una resposta a les ordres dels clients. Aquestes activitats estan relacionades amb les decisions d'acceptació/rebuig, i establiment de dates de lliurament per a les ordres del client. En les cadenes de subministrament afectades per la LHP, l'OPP ha de considerar l'homogeneïtat com un altre requisit addicional en la resposta a les comandes. A més, a causa de la incertesa intrínseca de la LHP, les discrepàncies entre les quantitats homogènies reals i planificades podrien provocar que les ordres compromeses anteriorment no puguen ser completades a causa de l'escassetat de producte. El procés de planificació de l'escassetat (SP, per les seues sigles de l'anglés "Shortage Planning") s'encarrega de trobar alternatives per a minimitzar aquest impacte negatiu en els clients i en la cadena de subministrament. Considerar la LHP dins de l'OPP implica un conjunt nou de característiques desafiants que han de ser abordades. L'enfocament convencional d'assumir l'homogeneïtat en el producte per al programa mestre de producció (MPS, per les seues sigles de l'anglés "Master Production Schedule") i les quantitats disponibles a comprometre (ATP, per les seues sigles de l'anglés "Available-To-Promise") derivades d'ell, no és adequat. En canvi, tant el MPS com l'ATP han de manejar-se en termes de sublots homogenis. Atés que la quantitat exacta de producte homogeni dels lots previstos en el MPS no se sap exactament fins que s'han realitzat les activitats de classificació, l'ATP també hereta aquesta incertesa, portant un nou nivell de complexitat. El producte no homogeni no es pot acumular per a satisfer futures ordees entrants. Més encara, si el producte manipulat és perible, el maneig de l'homogeneïtat es torna molt més complex. Açò es deu al fet que l'estat del producte és dinàmic en el temps, i variables relacionades com qualitat, preu, etc., podrien també canviar amb el temps. Aquesta situació pot provocar costos inesperats de rebuig a banda de l'escassetat ja esmentada. El factor de perible és en si mateix un altra font d'incertesa associada a la LHP. Aquesta dissertació proposa un marc conceptual i diferents models i eines de programació matemàtica, tant en entorns deterministes com d'incertesa, per a recolzar a l'OPP i SP considerant l'efecte de LHP. L'objectiu és proporcionar un compromís fiable amb les comandes dels clients a la recerca d'un alt nivell de servei no sols en la data i la quantitat esperades, sGrillo Espinoza, H. (2017). Advanced methods and models in uncertainty for the order promising process in supply chain characterized by the lack of homogeneity in product [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/91110TESISCompendi

Modelling performance management measures through statistics and system dynamics-based simulation

[EN] The objective of this paper is to establish a methodology that combines performance measurement, a statistical record of measures to identify any relations among them, and system dynamics-based simulation modeling with the aim of supporting operations decision systems. This methodology intends to provide the comprehensive analysis of performance in such a way that it also analyzes the sensitivity and optimization of certain metrics according to requirements in each case. In the literature, this appears as a poorly developed research area. Some relevant studies have been identified which have attempted this combination, but have not completely established it.Grillo-Espinoza, H.; Campuzano Bolarin, F.; Mula, J. (2018). Modelling performance management measures through statistics and system dynamics-based simulation. Direccion y Organizacion. 65:20-35. http://hdl.handle.net/10251/120641S20356

Key parameters for the analysis stage of internationalization of operations

[EN] In this paper, we identify the key parameters to consider in a decision model on internationalization of operations. In order to propose these parameters, the GLOBOPE framework was adopted as the basis of this work. This framework contemplates the three commonest challenges of global operations configuration for industrial manufacturing companies in an internationalization process, which are: new facility implementation (NFI); global suppliers' network development (GSND); multisite production network configuration. A set of suitable parameters is herein provided for NFI and GSND in the analysis stage from strategic, tactical and operational decision levels. These parameters could be used in the future as a basis for the development of quantitative tools for decision making on the internationalization of operations.This research has been funded by the Spanish Ministry of Science and Education project, entitled 'Operations Design and Management in Global Supply Chains (GLOBOP)' ( Ref. DPI2012-38061-C02-01).Grillo-Espinoza, H.; Mula, J.; Martinez, S.; Errasti, A. (2018). Key parameters for the analysis stage of internationalization of operations. Brazilian Journal of Operations & Production Management. 15:173-181. https://doi.org/10.14488/BJOPM.2018.v15.n2.a1S1731811

Application of particle swarm optimisation with backward calculation to solve a fuzzy multi-objective supply chain master planning model

Traditionally, supply chain planning problems consider variables with uncertainty associated with uncontrolled factors. These factors have been normally modelled by complex methodologies where the seeking solution process often presents high scale of difficulty. This work presents the fuzzy set theory as a tool to model uncertainty in supply chain planning problems and proposes the particle swarm optimisation (PSO) metaheuristics technique combined with a backward calculation as a solution method. The aim of this combination is to present a simple effective method to model uncertainty, while good quality solutions are obtained with metaheuristics due to its capacity to find them with satisfactory computational performance in complex problems, in a relatively short time period.This research is partly supported by the Spanish Ministry of Economy and Competitiveness projects '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) (Ref. DPI2011-23597) and 'Operations design and Management of Global Supply Chains' (GLOBOP) (Ref. DPI2012-38061-C02-01); by the project funded by the Polytechnic University of Valencia entitled 'Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics' (PAID-06-12); and by the Ministry of Science, Technology and Telecommunications, government of Costa Rica (MICITT), through the incentive program of the National Council for Scientific and Technological Research (CONICIT) (contract No FI-132-2011).Grillo Espinoza, H.; Peidro Payá, D.; Alemany Díaz, MDM.; Mula, J. (2015). Application of particle swarm optimisation with backward calculation to solve a fuzzy multi-objective supply chain master planning model. International Journal of Bio-Inspired Computation. 7(3):157-169. https://doi.org/10.1504/IJBIC.2015.069557S1571697

A review of mathematical models for supporting the order promising process under Lack of Homogeneity in Product and other sources of uncertainty

[EN] This paper presents a review of mathematical programming models for supporting the order promising process (OPP) under Lack of Homogeneity in Product (LHP) conditions and uncertainty in a modelling approach. LHP appears in productive processes with raw materials, which directly stem from nature and/or production processes with operations that confer heterogeneity to the characteristics of the out-puts obtained, even when the inputs used are homogenous. LHP has a direct impact on the company s service level, mainly when the customer needs to be served with homogeneous units of the same product. LHP leads to inherent sources of uncertainty due to the natural physical characteristics of the supply chain. This research aims to determine the way that LHP, and uncertainties related either to LHP or dif-ferent variables that confer more realistic conditions to OPP, have been modelled in different LHP sectors, or others affected by uncertainty. This result may provide the opportunity to transfer knowledge among them and to identify gaps for further research. Accordingly, and in order to set the basis for future research into the OPP topic, for cases affected by LHP and for uncertainties inherent to LHP conditions, or due to other possible uncertain variables, this research needs to consider both mathematical model types: (i) mathematical programming models of the OPP that consider some LHP characteristic and (ii) mathematical programming models of the OPP that consider any type of uncertainty in the modelling approach. We propose a taxonomy approach to classify and analyse the literature based on the main characteristics of its environment, order promising approach, customer order characteristics, modelling characteristics, and LHP and uncertainty modelling. The main finding of this research was that research into OPP modelling, combined with LHP characteristics and uncertainty, are lacking. We provide some starting points for further research in this field.This research has been partly supported by Spanish Ministry of Economy and Competitiveness Project '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) (Ref. DPI2011-23597), and by the Ministry of Science, Technology and Telecommunications, Government of Costa Rica (MICITT), through the program of innovation and human capital for competitiveness (PINN) (Contract No. PED-019-2015-1).Grillo-Espinoza, H.; Alemany Díaz, MDM.; Ortiz Bas, Á. (2016). A review of mathematical models for supporting the order promising process under Lack of Homogeneity in Product and other sources of uncertainty. Computers & Industrial Engineering. 91:239-261. https://doi.org/10.1016/j.cie.2015.11.013S2392619

A Fuzzy Order Promising Model With Non-Uniform Finished Goods

[EN] In this paper, in order to reliably meet the homogeneity required by customers, a fuzzy model is proposed to support the promising process in LHP contexts after taking into account uncertainty in planned homoge- neous sublots. The fuzzy model is translated into an alpha- parametric equivalent crisp model. Here, it is important to highlight another important novelty of the paper related to the proposed methodology to analyse the suitability of the minimum degree of possibility (the a-cut), by an adapted TOPSIS-based fuzzy procedure. Finally, the experimental design, which is inspired in the ceramic sector, proves both the validity of the model and a better performance of the fuzzy model compared to the deterministic one, in several executions with forecasts of the real size of homogeneous sublots.This research is partly supported by: The Ministry of Science, Technology and Telecommunications of the of Costa Rica Government (MICITT), through the Programme of Innovation and Human Capital for Competitiveness (PINN)(Contract No. PED-019-2015-1); and the Spanish Ministry of Economy and Competitiveness Projects "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) (Ref. DPI2011-23597) and "Operations design and Management of Global Supply Chains'' (GLOBOP) (Ref. DPI2012-38061-C02-01).Grillo-Espinoza, H.; Alemany Díaz, MDM.; Ortiz Bas, Á.; Mula, J. (2018). 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A fuzzy model for shortage planning under uncertainty due to lack of homogeneity in planned production lots

Lack of homogeneity in the product (LHP) affects several sectors like horticulture, reverse logistics, furniture, ceramics and leathers, among others. Productive processes with LHP are characterized by manufacturing units of the same finished good (FG) with certain attributes that differ and are relevant to customers. This aspect leads to the existence of different subtypes of the same FG in each production lot, which provides homogeneous sublots. Due to inherent LHP uncertainty, the size of each homogeneous sublot is not known until produced. LHP becomes a problem when customers order several units of the same FG and require homogeneity among them; i.e., being served with the same subtype. Like inherent LHP uncertainty, discrepancies between planned homogeneous quantities and the real ones is quite usual. This means it is impossible to serve committed orders with the previously defined requirements of quantity, homogeneity and due date, which brings about a shortage situation. In this paper, a fuzzy mixed integer linear programming model is proposed to support shortage planning in environments with LHP (LHP-FSP model). The LHP-FSP model aims to maximize the profits of served orders by reallocating the quantities of subtypes in stock and the uncertainty future ones in the master plan among the already committed orders. One of the main contributions of the paper is to model the fuzzy interdependent coefficients that represent the fraction of each homogeneous sublot. Finally, experiments based on realistic data from a ceramic company have been designed to validate the model and to analyze its behavior in different scenarios.This research has been carried out within the project framework funded by the Spanish Ministry of Economy and Competitiveness (Ref. DPI2011-23597) and the Universitat Politecnica de Valencia (Ref. PAID-06-11/1840) entitled "Methods and models for operations planning and order management in supply chains characterized by uncertainty in production due to the lack of product uniformity" (PLANGES-FHP).Alemany Díaz, MDM.; Grillo Espinoza, H.; Ortiz Bas, Á.; Fuertes Miquel, VS. (2015). A fuzzy model for shortage planning under uncertainty due to lack of homogeneity in planned production lots. Applied Mathematical Modelling. 39(15):4463-4481. https://doi.org/10.1016/j.apm.2014.12.057S44634481391

Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products

[EN] This paper proposes a mixed integer mathematical programming model to support the complex order promising process in fruit supply chains. Due to natural factors, such as land, weather or harvesting time, these supply chains present units of the same product that differ in certain relevant attributes to customers (subtypes). This becomes a manage- rial problem when customers require specific subtypes in their orders. Additionally, the de- terioration of the original characteristics of subtypes over time generates waste and gives rise to a shelf life-based pricing policy. Therefore, the developed model should ensure that customers are served not only the quantities and dates, but also the required homogene- ity and freshness. The model aims to maximise two conflicting objectives: total profit and mean product freshness. The novelty of the model derives from considering both homo- geneity in subtypes as a requirement in customer orders and the traceability of product deterioration over time. Different scenarios are defined according to the weight assigned to each objective, shelf-life length and pricing policy in a rolling horizon scheme. The nu- merical experiments conducted for a real orange and tangerine supply chain, show the model¿s validity and the conflicting behaviour of the two objectives. The highest profit is made at the expense of the lowest mean freshness delivered, which is reinforced by the narrower the price variation with freshness. Finally, the positive impact of prolonging the product¿s shelf life on both objectives is shown.This research has been partly supported by the Ministry of Science, Technology and Telecommunications, of the government of Costa Rica (MICITT), from the Spanish "Science, Technology and Telecommunications" through the programme of innovation and human capital for competitiveness (PINN) (contract number PED-019-2015-1), and by the Spanish Ministry of Economy and Competitiveness Project "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) (Ref. DPI2011-23597)Grillo Espinoza, H.; Alemany Díaz, MDM.; Ortiz Bas, Á.; Fuertes-Miquel, VS. (2017). Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products. Applied Mathematical Modelling. 49:255-278. https://doi.org/10.1016/j.apm.2017.04.037S2552784