Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551014
Pertenecen a esta colección Tesis y Trabajos de grado de los Doctorados correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
Browse
Search Results
- A reference framework for supplier 4.0 development programs in support of digital supply chain integration(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-11-25) Ricárdez Estrada, Josselyne; Garay Rondero, Claudia Lizette; emimmayorquin, emipsanchez; Wuest, Thorsten; Pinto, Roberto; Armando Elizondo Noriega; School of Engineering and Sciences; Campus Puebla; Romero Díaz, David C.In the Global Manufacturing sector, the Digital Transformation of Supply Chains (SCs) has reshaped the core principles of competitiveness, agility, and collaboration. Organisations that can effectively integrate technologies, data, and processes across the SC are most likely to sustain competitiveness and resilience. However, while Original Equipment Manufacturers (OEMs), commonly referred to as “focal companies”, have accelerated their transformation through advanced digital initiatives, a persistent gap remains in the digital readiness of their suppliers, particularly Small and Medium-sized Enterprises (SMEs). Many suppliers still operate without structured mechanisms to develop the Digital Capabilities (DCs) required to participate in emerging Digital Supply Chains (DSCs). This asymmetry limits not only the individual progress of suppliers but also the overall performance and adaptability of SCs as interconnected systems. Supplier Development Programs (SDPs) have historically played a central role in strengthening supplier performance and ensuring alignment with focal company requirements. However, most existing development programs remain anchored in traditional operational metrics such as cost, quality, delivery, and service, verlooking the strategic and technological dimensions of transformation required in the Industry 4.0 context. Although several digital maturity models and strategic frameworks for digital transformation exist, none have been specifically designed to guide the structured development of suppliers’ DCs in alignment with DSC Integration (DSCI). The lack of an integrative, reference framework continues to hinder coherent progress toward more intelligent, data-driven, and interconnected ecosystems. Hence, this dissertation addresses this gap by proposing the Supplier 4.0 Development Programs (S4.0DPs) Reference Framework, a comprehensive and iterative model that supports the design and implementation of SDPs focused on building the next generation of suppliers, referred to here as “Suppliers 4.0”. The S4.0DPs Reference Framework provides a structured approach for identifying, prioritising, and roadmapping suppliers’ DC development and support ntegration within DSCs. This conceptualisation enables the S4.0DPs Reference Framework to bridge theoretical fragmentation in scientific literature and offers a consistent reference for both scholars and practitioners. It standardises the understanding of what DCs entail for suppliers and provides a practical foundation for designing digital transformation strategies that enhance alignment and co-evolution between suppliers and focal companies. Methodologically, the Ph.D. thesis adopts the Design Science Research (DSR) approach, which combines scientific rigour with practical applicability through iterative design, validation, and evaluation. Three complementary methodological components support this process. First, a Scoping Literature Review (ScR) maps the existing body of knowledge on DSC transformation frameworks and suppliers’ digital transformation frameworks, identifying conceptual gaps and constructing the first version of the S4.0DPs Reference Framework. Second, a Delphi study involving international experts from industry and academia validates and refines the S4.0DPs Reference Framework’s elements, ensuring the robustness of its structure and the coherence of relationships among its components. Third, a Multi-Stakeholder Case Study in the automotive sector evaluates the practical feasibility and contextual adaptability of the S4.0DPs Reference Framework through the participation of a focal company and its Tier-1 suppliers. The insights derived from this component of the research methodology inform the development of an operational guideline that supports the real-world application of the S4.0DPs Reference Framework. The validated S4.0DPs Reference Framework consists of four phases and incorporates key influencing factors that guide suppliers’ progression towards “Supplier 4.0” status. The Ph.D. thesis’s findings contribute to theory and practice. From a theoretical perspective, this Ph.D. thesis advances the literature on DSC Management by reconceptualising suppliers’ development as a process of mutual learning, co-creation, and strategic alignment, rather than a unilateral mechanism of compliance. On the practical side, the proposed S4.0DPs Reference Framework offers managers an actionable tool to design and implement supplier development initiatives that foster digital maturity, enhance collaboration, and strengthen competitiveness across the SC. Ultimately, this Ph.D. thesis calls for a paradigm shift in the way SCs understand and operationalise suppliers’ development. By embedding the development of DCs within a logic of shared responsibility, collaboration, and adaptive learning, the S4.0DPs Reference Framework supports a transition towards more resilient, intelligent, and inclusive DSCs. It highlights that digital transformation is a strategic and relational process that redefines how value, trust, and knowledge circulate across DSCs. In this sense, this Ph.D. thesis contributes to shaping a future where digital integration becomes a shared pathway for competitiveness, resilience, and collective progress.
- Optimization and Simulation of a Defined Contribution Pension System for Faculty Under Certainty and Uncertainty(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-02-11) Montufar Benítez, Marco Antonio; Mora Vargas, Jaime; emimmayorquin; Gónzalez Mendoz, Miguel; School of Engineering and Sciences; Campus Estado de México; Muñoz Negrón, David FernandoIn recent years, the increasing complexity and risk exposure of pension systems have ledresearchers to adopt hybrid approaches that integrate simulation and optimization techniques to support strategic decisions. Simulation methods, particularly Monte Carlo and scenariobased simulations, have been widely applied to capture uncertainties related to asset returns, salary progression, interest rates, and mortality risk (Boulier et al., 1995; Haberman and Vigna, 2002). These simulations enable the modeling of dynamic systems over long horizons and provide insight into the stochastic nature of pension outcomes. Parallel to this, optimization techniques—especially stochastic control, dynamic programming, and quadratic programming—have been employed to derive optimal asset allocations and contribution strategies. For example, Cairns et al. (2006) introduce a stochastic lifestyling model for defined contribution plans, optimizing investment strategies based on salary risk and annuity constraints. Similarly, Consiglio et al. (2015) develop a stochastic programming model to design and price guarantee options in DC plans, balancing cost and embedded risks. Shen and Sherris (2017) extend these methods by integrating stochastic mortality, income, and interest rate models into a unified lifetime optimization framework. Their work illustrates how both idiosyncratic and systematic longevity risks influence investment, consumption, and insurance strategies over an individual’s ifetime. Together, these studies show that combining simulation with optimization provides a robust toolkit for assessing pension policy reforms, designing dynamic investment strategies, and evaluating guarantee mechanisms under demographic and financial uncertainty. This integrated approach enhances the capacity to make informed, resilient decisions that align long-term financial sustainability with retirees’ welfare. This work synthesizes a series of studies addressing pension planning for academic personnel at Mexican higher education institutions. The first study, presented at the 2020 ICPR-Americas conference, introduced a linear optimization model developed in LINGO to determine the minimum salary contribution rate required to ensure retirement coverage over a desired number of years. The model incorporates key economic variables such as inflation, salary increases, and interest rates. Results showed that a contribution rate of approximately 13% was necessary to provide sufficient retirement income over a 10- to 20-year post-retirement period. Building upon this foundation, the 2025 article in Computation presents a deterministic multi-objective optimization model designed to both minimize the ontribution rate and maximize post-retirement coverage. Implemented in LINGO, the model evaluates three realistic economic scenarios under varying inflation rates and retirement needs. It produces Pareto-optimal solutions, revealing that optimal contribution rates can range from 10% to 80% of salary depending on assumptions, particularly inflation and desired income replacement levels. The study published in 2024 in Computational Statistics, applies a stochastic simulation model using Arena software to analyze a defined contribution retirement scheme. The simulation incorporates faculty age, seniority, salary dynamics, and attrition probabilities. The results show that an increase in the number of simulation replicas significantly impacts the precision and stability of average capital estimates. When moving from 30 to 300 replicas, the mean capital increases from 479.79 to 509.46 thousand MXN, and the 90% confidence interval for this mean becomes noticeably narrower, shrinking from a range of [435.56, 524.03] to [495.21, 523.71] thousand MXN. This reduction in interval width is clear evidence of increased reliability in the average capital estimation. When simulating with 1000 replicas, the mean capital further stabilizes at 510.45 thousand MXN, and the 90% confidence interval contracts to an even more precise range of [502.75, 518.15] thousand MXN. This reaffirms that a higher number of simulations leads to a more robust estimate with less uncertainty. A consistent finding across all scenarios is the 5% Value at Risk (VAR 5%), which remains at 27.82 thousand MXN. This indicates that 5% of capital outcomes fall below this value, suggesting stability in the lower capital thresholds, regardless of the number of replicas used. Finally, the Coefficient of Variation (CV), although showing a slight decrease with more replicas (from 108.56% to 102.50%), consistently remains above 100%. This high CV underscores a considerable relative variability in the capital data. This elevated dispersion implies that, while the mean becomes more precise with more replicas, the intrinsic variability of teachers’ capital is a prominent characteristic that must be considered in risk assessment. In summary, the simulation results improve in precision and stability as the number of replicas increases, which is fundamental for informed decision-making within a pension system.. Together, these studies demonstrate the value of combining optimization and simulation techniques to inform institutional pension planning, offering robust tools for decision-makers navigating the evolving landscape of retirement systems in Mexico.
- Instant deliveries in Mexico City: a socio-economic analysis and profit maximization framework for couriers(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-11-27) Galindo Muro, Ana Bricia; Mora Vargas, Jaime; emipsanchez; Dablanc, Laetitia; Ugalde Monzalvo, Marisol; De Unanue Tiscareno, Adolfo Javier; School of Engineering and Sciences; Campus Ciudad de México; Cedillo Campos, Miguel GastónThis thesis introduces an engineering approach to understanding instant delivery operations within the platform economy. During the first step, through two surveys, the study highlighted couriers’ significant risks and challenges, shedding light on their precarious working conditions and financial pressures. The results emphasize the glaring disparity between the platform economy’s promise of flexibility and independence and the harsh reality experienced by most couriers. Furthermore, the study presents an assignment model to support technological advancements, which can lead to more effective decision-making, benefiting all actors involved in the urban instant delivery platform. By incorporating a fee algorithm and operational cost calculations, the quantitative model developed in this study demonstrates that a 20% increase in couriers’ income compared to traditional assignment models is advantageous for all parties. This approach seeks to raise awareness about the socioeconomic implications of emerging technologies such as Instant Deliveries and their regulation, particularly in rapidly developing urban areas. It offers valuable insights to build a more socially responsible and environmentally sustainable optimization approach in engineering.
- Commercial delivery policies: inventory management models with power demand pattern(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-06-29) Khan, Md. Al-Amin; Cárdenas Barrón, Leopoldo Eduardo; emiggomez, emipsanchez; Loera Hernández, Imelda de Jesús; Smith, Neale R.; Treviño Garza, Gerardo; Bourguet Díaz, Rafael Ernesto; School of Engineering and Sciences; Campus MonterreyIn the fast-paced, ever-changing environment of contemporary business, inventory management stands as a vital, ongoing endeavor. The discipline of decision-making in inventory management assumes a central role in this dynamic environment that is marked by continuous change and intense competition. Navigating the complexities of decision-making poses challenges, particularly in accurately assessing the multifaceted aspects of decision-making processes amid varying circumstances, including demand fluctuations, different types of discounts, and contractual agreements. At the same time, the increasing concern among consumers regarding the environmental footprint of their purchases, coupled with government-mandated regulations, complicates the decision-making process for businesses. In this milieu, sustainable inventory management practices have emerged as a pertinent research area, prompting heightened scrutiny of the impacts of emission guidelines on inventory practices, not only aimed at addressing broader societal concerns but also at ensuring the financial sustainability of businesses. This thesis adopts a specialized demand structure known as the power demand pattern (PDP) to depict fluctuations in demand over the storage period of a company, providing a robust framework for understanding customer demand dynamics across various products. The company maintains its inventory by acquiring items through quantity discounts in exchange for a quantity-sensitive prepayment as part of a contractual arrangement. This thesis introduces a novel concept by considering the installment frequency for fulfilling prepayment obligations as a decision variable for the company, incorporating a transaction fee for each installment. Furthermore, theoretical formulas are developed under different sorts of demand structures, incorporating the influences of selling price and storage time, to assess the profitability of inventory management processes under a combined link-to-order prepayment and quantity discount scheme. A significant advancement by integrating sustainability considerations into both inventory management and pricing strategies within the framework of the PDP is accomplished in this thesis. Through systematic identification and comparison of sustainable inventory management practices under varying emission guidelines, this study provides valuable insights aimed at optimizing profits within the PDP. Therefore, the insights derived from this study offer organizations practical techniques to navigate the complex regulatory environment effectively and achieve sustainable financial performance. Moreover, intensive and comprehensive in-depth sustainable inventory practices under the PDP are established specifically for growing items (GIs). This thesis investigates the impact of weight loss resulting from bleeding and non-consumable components on optimal pricing and inventory strategies for a farm, delving into previously unexplored areas within the literature on GIs. A comparative analysis is conducted on the operations of a livestock farm, operating within several environmental regulations. Consequently, the comprehensive methodology improves sustainable inventory management techniques and offers practical strategies to mitigate environmental impacts and enhance economic feasibility in livestock production.