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Start-up firms play an important role in the economy. Statistics show that a large percent of start-up firms fail after few years of establishment. Raising capital, which is crucial to success, is one of the difficulties start-up firms face. This Ph. D thesis aims to draw suggestions for start-up firm survival from mathematical models and numerical investigations. Instead of the commonly held profi t maximizing objective, this thesis assumes that a start-up firm aims to maximize its survival probability during the planning horizon. A firm fails if it runs out of capital at a solvency check. Inventory management in manufacturing start-up firms is discussed further with mathematical theories and numerical illustrations, to gain insight of the policies for start-up firms. These models consider specific inventory problems with total lost sales, partial backorders and joint inventory-advertising decisions. The models consider general cost functions and stochastic demand, with both lead time zero and one cases. The research in this thesis provides quantitative analysis on start-up firm survival, which is new to the literature. From the results, a threshold exists on the initial capital requirement to start-up firms, above which the increase of capital has little effect on survival probability. Start-up firms are often risk-averse and cautious about spending. Entering the right niche market increases their chance of survival, where the demand is more predictable, and start-ups can obtain higher backorder rates and product price. Sensitivity tests show that selling price, purchasing price and overhead cost have the most impact on survival probability. Lead time has a negative effect on start-up firms, which can be offset by increasing the order frequent. Advertising, as an investment in goodwill, can increase start-up firms' survival. The advertising strategies vary according to both goodwill and inventory levels, and the policy is more flexible in start-up firms. Externally, a slightly less frequency solvency check gives start-up firms more room for fund raising and/or operation adjustment, and can increase the survival probability. The problems are modelled using Markov decision processes, and numerical illustrations are implemented in Java.

The objective of this study was to examine the relationship between intensity of short-range and medium-range capacity management and effectiveness of manufacturing operations. Data were collected to test the null hypothesis which stated that intensity of short-range and medium-range capacity management does not influence manufacturing effectiveness. Intensity of short-range and medium-range capacity management was indicated by the following variables: (1) production standards; (2) priority determination; (3) delivery dates determination; (4) material requirements planning; (5) routing information; (6) capacity utilization; and (7) backlog measurement. Manufacturing effectiveness was indicated by the following variables: (1) delivery dates performance; (2) lead times; (3) subcontract work; (4) direct labor overtime; (5) direct labor efficiency; (6) plant and equipment utilization; and (7) work in process inventory. The population selected to provide data for this study is the manufacturing firms in the State of Texas with five hundred or more employees. Over 42 percent of the eligible firms responded to a six-page questionnaire. Several multivariate techniques were utilized for data analysis: (1) factor analysis; (2) canonical correlation analysis; (3) bivariate correlation; (4) multiple linear regression; (5) cross-tabulation; and (6) analysis of variance. The results of this research did not adequately support the rejection of the null hypothesis. However, they did definitely identify a distinct group of capacity management intensity variables that influence manufacturing effectiveness in specific cases. Intensity variables were placed in three groups that identified how influential they were over the effectiveness measures. The most influential group included the variables: production standards and material requirements planning. The indication for the manufacturing manager is to concentrate on improvements in these areas. Effectiveness variables were also placed in three groups that identified the level at which the variables were influenced by the intensity variables. The highly influenced group included plant and equipment utilization and delivery dates performance.

Inventories totaling 1.7 trillion U.S. dollars represent an opportunity for U.S. manufacturers. This exploratory case study researched supply chain strategies used to manage inventory in manufacturing operations of a U.S. manufacturing company. A mature value chain contained within a single organization using the value chain framework was the basis for this study. Individual interviews conducted with 16 managers responsible for defining and implementing inventory control strategies, and 4 internal users provided primary information for the study. Other sources of information included a value chain map created through the observation of operations, various inventory measurements, and policies and guidelines related to managing inventory levels. An inductive content analysis employing zero-level coding of the interview transcripts identified 4 themes that describe inventory control strategies as economic order quantity, kanban, vendor managed inventory, and process integration. Physical observation of the value chain, review of supporting documents, and analysis of inventory data ensured the trustworthiness of interpreted themes. Findings identified no single inventory control strategy that fit all applications. Findings also revealed that the financial governing bodies' measurements were not the best tools for operational managers' improvement activities related to inventory control. Included are measures providing alternative means to gauge inventory efficiency. With the results of this study, managers may develop effective strategies to optimize inventory and improve material flow. Manufacturing managers improving material flow may promote sustainability of raw materials and business efficiencies through reduced waste, improved environmental conditions, and increased employment opportunities in associated communities.

Prior research suggests that industry 4.0 could bring numerous benefits to firms manufacturing operations. Despite industry 4.0’s overwhelming popularity, there is considerable confusion surrounding how to approach a transformation, and additionally how it will affect organizations. Bus manufacturing has seen minor advancements in initiating change towards industry 4.0 due to characteristics with low volumes, high product varieties, high complexity and a large variety of customer adaptations. This thesis intends to give clarity to the opportunities and challenges that industry 4.0 technologies entail for bus manufacturing operations. Furthermore, contribute with a roadmap for how to manage a transformation towards industry 4.0 directed for bus manufacturing. The thesis was conducted studying a case using the process of systematic combining. Qualitative methods were applied to address the research questions, collecting data from ten interviews with operational- and manufacturing managers. Empirical findings indicate that the characteristics of bus manufacturing influence the industry 4.0 technologies that are applicable and suited for implementation. The findings suggest opportunities in terms of increased production efficiency, improved flexibility and reduced takt times with data management and real-time capabilities from adapting data management, cloud technology and sensors. Other opportunities such as virtualization with digital twin and virtual training were also suggested to enable factory simulations and virtual representations of manufacturing stations. Prominent challenges identified were lack of knowledge regarding industry 4.0 technologies, data analytics, how to motivate investments, system integration and using robotics in the bus manufacturing operations. Furthermore, the proposed roadmap for how bus manufacturing can manage a transformation towards industry 4.0 consists of eight steps that include important factors identified from the study such as vision, determination, barriers, responsibility, consistency and working in small steps. This study’s theoretical contribution is providing knowledge about industry 4.0 in the context of bus manufacturing operations. The findings suggest that knowledge is a primary factor for managing a transformation towards industry 4.0, where educating and engaging personnel could facilitate the change work. Further, the results of this study lend support to the argument that approaching industry 4.0 is dependent on the organization and industry. The study also emphasizes that future research should focus on establishing a uniform definition of industry 4.0, and further examine what the costs for a transformation towards industry 4.0 could necessitate for bus manufacturing operations. / Tidigare forskning tyder på att industri 4.0 kan ge många fördelar för företag som bedriver tillverkningsverksamhet. Trots industri 4.0’s överväldigande popularitet finns det betydande förvirring kring hur man närmar sig en transformation, samt hur det kommer att påverka organisationer. Busstillverkningsindustrin har sett en obetydlig utveckling i förändringsarbetet mot industri 4.0 på grund av dess egenskaper med låga volymer, stora variationer, höga komplexitet samt många kundanpassningar. Denna uppsats har för avsikt att klargöra de möjligheter samt utmaningar som teknologier inom industri 4.0 innebär för verksamheten inom busstillverkning, då industri 4.0 anses medföra stora förändringar inom produktionen. Studien bidrar vidare till en färdplan för hur man kan hantera en omvandling mot industri 4.0 inriktad för busstillverkning. Studien genomfördes genom att studera ett fall med tillvägagångssätt enligt “systematic combining”. Kvalitativa metoder tillämpades för att kunna behandla forskningsfrågorna med datainsamling från tio intervjuer med operativa- och produktionschefer. Empirin indikerar att kännetecknen för busstillverkning påverkar vilka teknologier inom industri 4.0 som är tillämpbara och lämpliga för implementering. Analys av empirisk data tyder på möjligheter i form av ökad produktionseffektivitet, flexibilitet samt reducerad takttid genom datahantering och real-tidsfunktioner från användning av artificiell intelligens, molnteknik samt sensorer. Ytterligare möjligheter antyddes inom virtualisering med digitala tvillingar samt virtuell träning för att simulera fabriken och produktionsstationer i virtuella miljöer. Framträdande utmaningar som antyddes var brist på kunskap om teknologierna inom industri 4.0, att analysera stora mängder data, att kunna motivera investeringar, systemintegration samt tillämpningen av robotik i produktionen. Den föreslagna färdplanen för hur busstillverkning kan hantera en omvandling mot industri 4.0 består av åtta steg som inkluderar viktiga faktorer som identifierades från studien såsom vision, beslutsamhet, hinder, ansvarighet, kontinuitet samt att arbeta i små steg. Det teoretiska bidraget från studien är kunskap om industri 4.0 i kontexten för busstillverkning. Resultatet tyder på att kunskap är en primär faktor för att hantera en förändring mot industri 4.0, där informera och engagera personal kan underlätta förändringsarbetet. Resultaten av denna studie ger stöd till argumentet att hur man närmar sig industri 4.0 är beroende av organisationen samt inom vilken industri som verksamheten bedrivs inom. Studien understryker även att framtida forskning bör fokusera på att skapa en enhetlig definition av industri 4.0, samt att vidare undersöka de kostnader som bussproduktion kan kräva vid en förändring mot industri 4.0.

Tesis por compendio / [ES] La gestión sostenible de las cadenas de suministro se ha transformado en un tema de alto interés entre profesionales e investigadores en el ámbito de la ingeniería industrial. El impacto que generan las actividades económicas en el medioambiente y en las comunidades donde éstas se ubican ha generado un incremento en el desarrollo de herramientas que permitan incorporar dichos impactos en las decisiones tomadas en el nivel estratégico de las empresas e industrias. Es así como surgen nuevos paradigmas respecto al modelo de producción, como por ejemplo la economía circular, donde se busca transitar desde una economía de producción lineal, hacia una circular reduciendo al mínimo la generación de desperdicios, ya sea material y/o energético. En este contexto, esta tesis doctoral, sustentada en una revisión de la literatura y en un análisis de modelos de optimización matemática de referencia, propone un marco conceptual como herramienta de soporte para seguir desarrollando modelos cuantitativos para dar soporte a los problemas de localización, inventario y transporte (LIT) en cadenas de suministro sostenibles, así como, un modelo de optimización multiobjetivo no lineal entero mixto (MOMINLP) para diseñar una cadena de suministro sostenible de bucle cerrado considerando las decisiones LIT, donde los aspectos de sostenibilidad: económico, medioambiental y social son incorporados en cada una de las decisiones anteriores. El modelo propuesto, denominado 3S-LIT, considera cuatro funciones objetivo que pretenden: (1) minimizar el coste total de la cadena de suministro; (2) minimizar los costes asociados a la emisión de CO2 equivalente; (3) minimizar el coste social relacionado con los accidentes laborales; y (4) maximizar el impacto social, medido como el incremento en cuanto a la generación de empleos directos e indirectos y la reducción en la cantidad de personas afectas por los riesgos del transporte dentro de la cadena de suministro. El modelo 3S-LIT ha sido validado en una empresa del sector minero del cobre obteniendo un mejor desempeño en los valores de las funciones objetivo respecto a los obtenidos en la situación actual. Además, el modelo 3S-LIT se ha comparado con un enfoque existente en la literatura científica obteniéndose unos resultados satisfactorios tanto en términos de funcionalidades como de resultados. Finalmente, el modelo propuesto de optimización matemática, 3S-LIT, es replicado en un modelo de simulación con el cual se estudiaron posibles escenarios de disrupción de la cadena de suministro con el objetivo de analizar su capacidad resiliente. / [CA] La gestió sostenible de les cadenes de subministrament s'ha transformat en un tema d'alt interès entre professionals i investigadors en l'àmbit de l'enginyeria industrial. L'impacte que generen les activitats econòmiques en el medi ambient i en les comunitats on aquestes se situen ha generat un increment en el desenvolupament d'eines que permeten incorporar aquests impactes en les decisions preses en el nivell estratègic de les empreses i indústries. És així com sorgeixen nous paradigmes respecte al model de producció, com per exemple l'economia circular, on se cerca transitar des d'una economia de producció lineal, cap a una circular reduint al mínim la generació de desaprofitaments, ja siga material i/o energètic. En aquest context, aquesta tesi doctoral, sustentada en una revisió de la literatura i en una anàlisi de models d'optimització matemàtica de referència, proposa un marc conceptual com a eina de suport per a continuar desenvolupant models quantitatius per a donar suport als problemes de localització, inventari i transport (LIT) en cadenes de subministrament sostenibles, així com, un model d'optimització multi-objectiu no lineal enter mixt (MOMINLP) per a dissenyar una cadena de subministrament sostenible de bucle tancat considerant les decisions LIT, on els aspectes de sostenibilitat: econòmic, mediambiental i social són incorporats en cadascuna de les decisions anteriors. El model proposat, denominat 3S-LIT, considera quatre funcions objectiu que pretenen: (1) minimitzar el cost total de la cadena de subministrament; (2) minimitzar els costos associats a l'emissió de CO2 equivalent; (3) minimitzar el cost social relacionat amb els accidents laborals; i (4) maximitzar l'impacte social, mesurat com l'increment quant a la generació d'ocupacions directes i indirectes i la reducció en la quantitat de persones afectes pels riscos del transport dins de la cadena de subministrament. El model 3S-LIT ha sigut validat en una empresa del sector miner del coure obtenint un millor acompliment en els valors de les funcions objectiu respecte als obtinguts en la situació actual. A més, el model 3S-LIT s'ha comparat amb un enfocament existent en la literatura científica obtenint-se uns resultats satisfactoris tant en termes de funcionalitats com de resultats. Finalment, el model proposat d'optimització matemàtica, 3S-LIT, és replicat en un model de simulació amb el qual es van estudiar possibles escenaris de disrupció de la cadena de subministrament amb l'objectiu d'analitzar la seua capacitat resilient. / [EN] Sustainable supply chain management has become a topic of great interest among practitioners and researchers in the field of industrial engineering. The impact generated by economic activities on the environment and the communities where they are located has generated an increase in the development of tools that allow the incorporation of these impacts in the decisions taken at the strategic level of companies and industries. This is how new paradigms emerge regarding the production model, such as the Circular Economy, which seeks to move from a linear production economy to a circular one by minimising the generation of waste, both material and energetic. In this context, this PhD thesis, supported by a state-of-the-art study and the analysis of benchmark mathematical optimisation models, presents a conceptual framework to provide the key elements that act as a valuable tool to further develop quantitative models of location, inventory and transport (LIT) problems in sustainable supply chains, and a novel mixed integer non-linear multi-objective mixed integer multi-objective optimisation model (MOMINLP) for designing a closed-loop sustainable supply chain considering location, inventory and transportation decisions, where economic, environmental and social sustainability aspects are incorporated in each of the above mentioned decisions. The proposed model, called 3S-LIT, considers four objective functions that aim to: (1) minimise the total cost of the supply chain, (2) minimise the costs associated with CO2 equivalent emissions, (3) minimise the social cost related to occupational accidents, and (4) maximise the social impact, measured as a higher generation of direct and indirect jobs and a lower number of people affected by transport risks within the chain. The 3S-LIT model has been applied in a company in the copper mining sector, confirming a better performance in the values of the objective functions compared to those obtained in the current situation. In addition, the mathematical optimisation model is replicated in a simulation model with which possible supply chain disruption scenarios were studied to analyse the resilience of the supply chain. / This thesis has been developed within the Research Centre on Production Management and Engineering (CIGIP) of the Universitat Politècnica de València, within the framework of the projects: "Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/2021/065) granted by the Valencian Regional Government and received funding from Grant RTI2018-101344-B-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”; “Validation of transferable results of optimisation of zero-defect enabling production technologies for supply chain 4.0” (CADS4.0-II) from the grant PDC2022-133957-I00; and by European Union Next GenerationEU/PRTR, and from the European Union’s Horizon Europe research and innovation programme under grant agreement No. 101070076 "Optimizing Production and Logistic Resources in the Time-critical Bio Production Industries in Europe" (CLARUS). It was also funded by the National Agency for Research and Development (ANID)/Scholarship Program/Doctorado Becas en el Extranjero/2020 – 72210174 and sponsored by the Universidad de Atacama as part of an academic improvement plan. / Becerra Muñoz, PA. (2023). Quantitative Models of Location, Inventory and Transportation Decisions for Sustainable Supply Chain Management [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/196651 / Compendio