F.-Javier Heredia - Academic web site

Publication Type	Funded research projects
Year of Publication	2020
Authors	F.-Javier Heredia
Type of participation	Leader
Duration	06/2020-12/2020
Funding organization	Top Cable
Partners	-
Project code	C-11622
Key Words	research; one dimensional cutting stock; private; project; manufacturing
Abstract	L’empresa Top Cable, líder en la fabricació de cables elèctrics, es planteja aplicar una millora en el seu ERP de gestió del magatzem, afegint-hi un nou mòdul que optimitzi i doni suggeriments a la logística del magatzem tenint en compte les noves arribades i l’stock que hi hagi present.
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Publication Type	Conference Paper
Year of Publication	2018
Authors	Daniel Ramón-Lumbierres; F.-Javier Heredia; Robert Gimeno Feu; Julio Consola; Román Buil Giné
Conference Name	23th International Symposium on Mathematical Programming
Conference Date	01-06/07/2018
Conference Location	Bordeaux
Editor	Mathematical Optimization Society (MOS)
Type of Work	contributed presentation
Key Words	research; supply chain; postponment; multistage stochastic programming
Abstract	Supply chain management has been widely developed through the evolution of manufacturing, distribution, forecasting and customer behavior, encouraging the introduction of postponement strategies in its various forms. At these strategies, semi-finished goods are stored in certain operations of the chain, called decoupling points, waiting for the placement of demand orders, which trigger production flows from decoupling points to the remainder operations. Such a design problem facing the speculation/postponement paradigm must intrinsically include elements that "unveil" demand orders when they are placed, that is, the modelling approach should keep demand orders as random variables until their placement, when they are disclosed. This work proposes a multi-stage stochastic programming model that decides the optimal allocation of decoupling points, as well as a process selection among alternative designs for any general supply chain case, where the stochastic parameters, demands by period and product, are represented through a scenario tree, which is in turn generated using the forecasting. Both a risk-neutral model and a risk-aversion approach with stochastic dominance constraints are presented and solved with multi-stage instances of test cases based on real manufacturing problems defined in collaboration with the Accenture consultancy company.
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Publication Type	Conference Paper
Year of Publication	2018
Authors	F.-Javier Heredia
Conference Name	Maths for Industry 4.0
Conference Date	19/02/2018
Conference Location	Barcelona
Type of Work	Round table
Key Words	research,; industrial mathematics; industry 4.0; BGSMath
Abstract	“Maths for Industry 4.0” will showcase how academic excellence at BGSMath is helping companies becoming digital. Join us to learn about successful collaborative initiatives, such as industrial doctoral theses, as well as the range of expertise you could benefit from. The workshop will be closed by a round table on Data Analytics. Our experts will discuss common challenges and trends across sectors, and how mathematical creativity enable solutions for supply chain, risk management, control and monitoring. This activity belongs to the Mobile Week Barcelona and it’s an open space for reflexion on digital transformation through art, science and technology.
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The Barcelona Graduate School of Mathematics (BGSMath ) organized last February 19 2018 the workshop "Maths for Industry 4.0 " to showcase how academic excellence at BGSMath is helping companies becoming digital through several successful collaborative initiatives, such as industrial doctoral theses or consultancy and development projects of the BGSMaths's research groups in Data Science and Optimization. The workshop will be closed by the round table "Optimising data analytics for industry 4.0" where I was invited to participate as expert in supply chain optimization. This activity is embedded into the Mobile Week Barcelona and it's an open space for reflexion on digital transformation through art, science and technology. More photos of the event at this link .

A new result of the research project Digitalizing Supply Chain Strategy with 3D Printing with Accenture TechLabs and Center for Analytics has been presented in the Manufacturing Engineering Society International Conference 2017 , MESIC 2017. The study compares different possible production strategies for a product (via conventional technologies and Additive Manufacturing) and assesses the degree of postponement that it would be recommended in order to meet a certain demand distribution. The problem solving is calculated by a program containing a stochastic mathematical model which incorporates extensive information on costs and lead times for the required manufacturing operations. This study was published in Procedia Manufacturing.  

Publication Type	Proceedings Article
Year of Publication	2017
Authors	J. Minguella-Canela; A. Muguruza; D.R. Lumbierres: F.-Javier Heredia; R. Gimeno; P. Guo; M. Hamilton; K.Shastry, S.Webb
Conference Name	Manufacturing Engineering Society International Conference 2017, MESIC 201
Series Title	Procedia Manufacturing
Volume	13
Pagination	754-761
Conference Start Date	18/06/2017
Publisher	Elsevier
Conference Location	Vigo, Spain
Editor	Jorge Salguero, Enrique Ares
ISSN Number	2351-9789
Key Words	Additive Manufacturing; Ultra-postponement; Supply Chain; research; paper
Abstract	The best-selling products manufactured nowadays are made in long series along rigid product value chains. Product repetition and continuous/stable manufacturing is seen as a chance for achieving economies of scale. Nevertheless, these speculative strategies fail to meet special customer demands, thus reducing the effective market share of a product in a range. Additive Manufacturing technologies open promising product customization opportunities; however, to achieve it, it is necessary to delay the production operations in order to incorporate the customer’s inputs in the product materialization. The study offered in the present paper compares different possible production strategies for a product (via conventional technologies and Additive Manufacturing) and assesses the degree of postponement that it would be recommended in order to meet a certain demand distribution. The problem solving is calculated by a program containing a stochastic mathematical model which incorporates extensive information on costs and lead times for the required manufacturing operations.
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DOI	https://doi.org/10.1016/j.promfg.2017.09.181
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Publication Type	Conference Paper
Year of Publication	2017
Authors	J. Minguella-Canela; A. Muguruza; D.R. Lumbierres; F.-Javier Heredia; R. Gimeno; P. Guo; M. Hamilton; K. Shastry; S. Webb
Conference Name	Manufacturing Engineering Society International Conference 2017, MESIC 2017, 28-30
Conference Date	28-30/07/2017
Publisher	Elsevier
Conference Location	Vigo, Spain
Type of Work	Contributed presentation
Key Words	research; Additive Manufacturing; Ultra-postponement; Supply Chain; stochastic programming
Abstract	The best-selling products manufactured nowadays are made in long series along rigid product value chains. Product repetition and continuous/stable manufacturing is seen as a chance for achieving economies of scale. Nevertheless, these speculative strategies fail to meet special customer demands, thus reducing the effective market share of a product in a range. Additive Manufacturing technologies open promising product customization opportunities; however, to achieve it, it is necessary to delay the production operations in order to incorporate the customer’s inputs in the product materialization. The study offered in the present paper compares different possible production strategies for a product (via conventional technologies and Additive Manufacturing) and assesses the degree of postponement that it would be recommended in order to meet a certain demand distribution. The problem solving is calculated by a program containing a stochastic mathematical model which incorporates extensive information on costs and lead times for the required manufacturing operations.
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Publication Type	Funded research projects
Year of Publication	2016
Authors	F.-Javier Heredia
Type of participation	Leader
Duration	11/2016-11/2019
Funding organization	Accenture Technology Labs
Partners	Accenture Technology Labs (Silicon Valley), Accenture Analytics Innovation Center (Barcelona)
Full time researchers	2
Budget	132.532,43€
Project code	I-01507, I-01508
Key Words	research; supply chain; manufacturing; private; project; Accenture
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Publication Type	Proceedings Article
Year of Publication	2016
Authors	Miguel Mata Perez; F.-Javier Heredia; Claudia Morales Carreon
Conference Name	Congreso Internacional de Logística y Cadena de Suministro 2016 CILOG2016
Series Title	Sesiones técnicas
Volume	2
Pagination	38-46
Conference Start Date	3-7/09/2016
Publisher	Asociación Mexicana de Logística y Cadena de Suministro A.C.
Conference Location	Yucatán, México
Key Words	research; supply chain; distribution chain; logistics; paper
Abstract	Hoy en día los costos logísticos representan una gran oportunidad de mejora para las empresas siendo los costos de transporte y los costos de inventario los más representativos. En este trabajo se presenta un estudio de una empresa ubicada en la región, la cual incurre actualmente en altos costos logísticos en su proceso de importación de materia prima desde Asia hasta su filial en Monterrey, N.L. Por medio de un modelo matemático entero mixto se consigue minimizar los costos antes mencionados. El modelo tiene las siguientes características: es de ubicación de facilidades en cuatro etapas, multiproducto, multiperiodo y multitransporte.
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