The priorities of executing the manufacturing orders generated by an MRP system are often in operational conflicts with the dynamics of the manufacturing floor. It is not uncommon for a given manufacturing order to reach the shop floor several weeks or longer after being "opened" by an MRP system where it may face a chaotic case of large queues, machine down-time, parts shortage, scrap problems and other resource management constraints. Many companies have resorted to the Manufacturing Execution System (MES) software solution to resolve these problems. This method first gained popularity in mid-90’s within the semiconductor industry. An MES approach is an on-line, real-time data gathering, analysis and storage to assist in short-interval scheduling (shift or day) manufacturing operations with an emphasis on revising scheduling priorities. It is essentially an information system tool for the shop floor and if designed properly, it may be used as an advisory system for effective decision-making. However, in implementation MES faces several challenges including the proper software platform/architecture, integration within ERP or a stand-alone best-of-breed, amount and type of data/information to be exchanged with the MRP engine, and a user-centered interface for various layers of decision making. This paper will provide a detailed background on various technical, software, and organizational factors that the use of an MES implementation may impose upon the practitioner. Furthermore, and as a case study, it will discuss a systematic implementation strategy for MES at a high-tech company in California. The discussion of the critical success factors in implementation planning will hopefully be of value to both practitioners and researchers in similar projects.

In today’s society, it is increasingly important for retailers to have an online presence, yet the adoption rate of e-commerce by small retailers is still lagging behind the that of larger retailers. This is due to the difficulty small retailers have to overcome the barriers to develop their web-shops, such as cost and time. This thesis will examine the barriers of single-store independent retail businesses to sell and market their goods online. It will use the Technology Acceptance Model framework developed by Davis (1986) to help understand how the barriers affect the retailers attitude towards the process of developing their web-shops. Specifically, it will ask the retailers, through interviews, what barriers exist, what their perception of difficulty to overcome these barriers is, and what their perception of importance to overcome these barriers is. The major findings show that the barriers for retailers have not changed in the past decade, nor has the difficulty level of overcoming these barriers. The majority of small retailers who have not yet developed their web-shops don’t feel that the effort to do so is worth the potential gains, yet the small retailers who have already developed their web-shops did feel it was worth the effort. The retailers all felt that the process was more difficult than it should be, and insisted they would make the leap if the cost and effort required was reduced.

No description available.

No description available.

As the Army transitions to the Army Force Generation (ARFORGEN) deployment cycle, it must adjust its many operations in support of ARFORGEN. Specifically, the Initial Military Training (IMT) must be able to adjust the scheduling of its classes for newly enlisted service members to finish training such that they fulfill Brigade Combat Team (BCT) requirements within their common due windows. We formulate this problem as a lot streaming problem. Lot streaming splits a batch of jobs into sublots,which are then processed over the machines in an overlapping fashion. To schedule classes for the IMT, there are two stages that must be coordinated: Basic Training (BT) and Advanced Individual Training (AIT). For the Army Force Generation problem, the classes are considered as sublots that are streamed from one stage to the next. For this process, the model formulation must address determination of class sizes and scheduling of soldiers and classes at the two stages such that (1) the start times of the soldiers at Stage 2 are greater than their completion times at Stage 1, and (2) the assignment of requisite number of soldiers is made to each BCT, so as to minimize the total flow time. We propose a decomposition-based approach for the solution of this problem. In an effort to decompose the problem, the original lot streaming problem is reformulated such that the master problem selects an optimal combination of schedules for training classes and assigning soldiers to BCTs. A complete schedule selected in the master problem includes the assignments of soldiers to classes in BT, AIT, and their assignments to the BCTs, so as to minimize the total flow time as well as earliness and tardiness for regular Army units. Earliness and Tardiness are defined as the length of the time a soldier waits before and after the due date, respectively, of the BCT to which he or she is assigned. Our decomposition-based method enables solution of larger problem instances without running out of memory, and it affords CPU time reductions when compared with the CPU times required for these problem instances obtained via direct application of CPLEX 12.1. Our investigation into the structure of the problem has enabled further improvement of the proposed decomposition-based method. This improvement is achieved because of a result, which we show, that the first and second-stage scheduling problems need not be solved as one combined subproblem, but rather, they can be solved sequentially, the first stage problem followed by the second stage problem. The combination of Stage 1 and Stage 2 problems as one subproblem creates several additional enumerations of possible schedules the model must generate. By reducing this number of enumerations, the computational effort involved in solving the model reduces significantly, thereby allowing reductions in CPU time. In the Sequential approach, the completion times of soldiers determined at Stage 1 are passed to Stage 2 as bounds on their completion times at Stage 2. We prove that solving the combined subproblem sequentially as two subproblems is optimal when the first stage has no limit on the batch size and the ready times of the soldiers at Stage 1 are the same. For the Army Force Generation problem, we use unequal ready times, and therefore, solving the scheduling problems for the first two stages as sequential subproblems can lead to suboptimal solutions. Our experimental investigation shows efficacy of solving larger-sized problem instances with this method. We also recommend various potential additions to improve the Sequential approach for application to the overall Army problem. We have also demonstrated the use of our methodology to a real-life problem instance. Our methodology results in schedules for IMT with an estimated 28% reduction in mean flow time for soldiers over what is currently experienced in practice. We apply this Sequential approach to various extensions of the problem on hand that pertain to hybrid flow shop and agile manufacturing environments. Results of our computational investigation show the effectiveness of using the Sequential approach over direct solution by CPLEX from the viewpoint of both optimality gap and the CPU time required. In particular, we consider two different model configurations for a hybrid flow shop and three different model configurations for an agile manufacturing facility. / Ph. D.

[ES] En esta Tesis Doctoral se aborda el problema del taller de flujo de permutación considerando recursos adicionales renovables, que es una versión más realista del clásico problema de taller de flujo de permutación, muy estudiado en la literatura. La inclusión de los recursos ayuda a acercar el mundo académico-científico al mundo real de la industria. Se ha realizado una completa revisión bibliográfica que no se ha limitado a problemas del taller de flujo, sino que han revisado problemas similares del ámbito de scheduling que consideren recursos. En esta revisión, no se han encontrado en la literatura artículos para el problema concreto que se estudia en esta tesis. Por ello, la aportación principal de esta Tesis Doctoral es el estudio por primera vez de este problema y la propuesta y adaptación de métodos para su resolución. Inicialmente, el problema se modeliza a través de un modelo de programación lineal entera mixta (MILP). Dada la complejidad del problema, el MILP es capaz de resolver instancias de un tamaño muy pequeño. Por ello, es necesario adaptar, diseñar e implementar heurísticas constructivas y metaheurísticas para obtener buenas soluciones en un tiempo de computación razonable. Para evaluar la eficacia y eficiencia de los métodos propuestos, se generan instancias de problemas partiendo de los conjuntos más utilizados en la literatura para el taller de flujo de permutación. Se utilizan estas instancias propuestas tanto para calibrar los distintos métodos como para evaluar su rendimiento a través de experimentos computacionales masivos. Los experimentos muestran que las heurísticas propuestas son métodos sencillos que consiguen soluciones factibles de una forma muy rápida. Para mejorar las soluciones obtenidas con las heurísticas y facilitar el movimiento a otros espacios de soluciones, se proponen tres metaheurísticas: un método basado en búsqueda local iterativa (ILS), un método voraz iterativo (IG) y un algoritmo genético con búsqueda local (HGA). Todos ellos utilizan las heurísticas propuestas más eficaces como solución o soluciones iniciales. Las metaheurísticas obtienen las mejores soluciones utilizando tiempos de computación razonables, incluso para las instancias de mayor tamaño. Todos los métodos han sido implementados dentro de la plataforma FACOP (Framework for Applied Combinatorial Optimization Problems). Dicha plataforma es capaz de incorporar nuevos algoritmos de optimización para problemas de investigación operativa relacionados con la toma de decisiones de las organizaciones y está diseñada para abordar casos reales en empresas. El incorporar en esta plataforma todas las metodologías propuestas en esta Tesis Doctoral, acerca el mundo académico al mundo empresarial. / [CA] En aquesta Tesi Doctoral s'aborda el problema del taller de flux de permutació considerant recursos addicionals renovables, que és una versió més realista del clàssic problema de taller de flux de permutació, molt estudiat a la literatura. La inclusió dels recursos ajuda a apropar el món acadèmic-científic al món real de la indústria. S'ha realitzat una revisió bibliogràfica completa que no s'ha limitat a problemes del taller de flux, sinó que ha revisat problemes similars de l'àmbit de scheduling que considerin recursos. En aquesta revisió, no s'ha trobat a la literatura articles per al problema concret que s'estudia en aquesta tesi. Per això, l'aportació principal d'aquesta Tesi Doctoral és l'estudi per primera vegada d'aquest problema i la proposta i l'adaptació de mètodes per resoldre'ls. Inicialment, el problema es modelitza mitjançant un model de programació lineal sencera mixta (MILP). Donada la complexitat del problema, el MILP és capaç de resoldre instàncies d'un tamany molt petita. Per això, cal adaptar, dissenyar i implementar heurístiques constructives i metaheurístiques per obtenir bones solucions en un temps de computació raonable. Per avaluar l'eficàcia i l'eficiència dels mètodes proposats, es generen instàncies de problemes partint dels conjunts més utilitzats a la literatura per al taller de flux de permutació. S'utilitzen aquestes instàncies proposades tant per calibrar els diferents mètodes com per avaluar-ne el rendiment a través d'experiments computacionals massius. Els experiments mostren que les heurístiques proposades són mètodes senzills que aconsegueixen solucions factibles de manera molt ràpida. Per millorar les solucions obtingudes amb les heurístiques i facilitar el moviment a altres espais de solucions, es proposen tres metaheurístiques: un mètode basat en cerca local iterativa (ILS), un mètode voraç iteratiu (IG) i un algorisme genètic híbrid (HGA). Tots ells utilitzen les heurístiques proposades més eficaces com a solució o solucions inicials. Les metaheurístiques obtenen les millors solucions utilitzant temps de computació raonables, fins i tot per a les instàncies més grans. Tots els mètodes han estat implementats dins de la plataforma FACOP (Framework for Applied Combinatorial Optimization Problems). Aquesta plataforma és capaç d'incorporar nous algorismes d'optimització per a problemes de recerca operativa relacionats amb la presa de decisions de les organitzacions i està dissenyada per abordar casos reals a empreses. El fet d'incorporar en aquesta plataforma totes les metodologies proposades en aquesta Tesi Doctoral, apropa el món acadèmic al món empresarial. / [EN] In this Doctoral Thesis, the permutation flowshop problem is addressed considering additional renewable resources, which is a more realistic version of the classic permutation flowshop problem, widely studied in the literature. The inclusion of resources helps to bring the academic-scientific world closer to the real world of industry. A complete bibliographic review has been carried out that has not been limited to flow shop problems, but has reviewed similar problems in the scheduling field that consider resources. In this review, no articles have been found in the literature for the specific problem studied in this thesis. Therefore, the main contribution of this Doctoral Thesis is the study for the first time of this problem and the proposal and adaptation of methods for its resolution. Initially, the problem is modeled through a mixed integer linear programming (MILP) model. Given the complexity of the problem, the MILP is capable of solving very small instances. Therefore, it is necessary to adapt, design and implement constructive heuristics and metaheuristics to obtain good solutions in a reasonable computation time. In order to evaluate the effectiveness and efficiency of the proposed methods, problem instances are generated starting from the sets most used in the literature for the permutation flowshop. These proposed instances are used both to calibrate the different methods and to evaluate their performance through massive computational experiments. Experiments show that proposed heuristics are simple methods that achieve feasible solutions very quickly. To improve the solutions obtained with the heuristics and facilitate movement to other solution spaces, three metaheuristics are proposed: a method based on iterated local search (ILS), an iterative greedy method (IG) and a hybrid genetic algorithm (HGA). All of them use the most effective proposed heuristics as initial solution or solutions. Metaheuristics get the best solutions using reasonable computation times, even for the largest instances. All the methods have been implemented within the FACOP platform (Framework for Applied Combinatorial Optimization Problems). Said platform is capable of incorporating new optimization algorithms for operational research problems related to decision-making in organizations and it is designed to address real cases in companies. Incorporating in this platform all the methodologies proposed in this Doctoral Thesis, brings the academic world closer to the business world. / Alfaro Fernández, P. (2023). Inteligencia computacional en la programación de la producción con recursos adicionales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/198891

The thesis dwells about methodics of processing an order in the company: Hardening shop Frydrych s.r.o. while respecting all the demands on the technological process of thermal and thermo-chemical manipulation as annealing, tempering and cementing. On the bases of the analyse and documental procedures the thesis is unraveling a concept for elimination of absences in the sphere of processing the order also as booking, invoicing and evaluating.

The central thesis of this dissertation is that by combining classical scheduling methodologies with those of inventory management and queueing theory we can better model, understand and solve complex real-world scheduling problems. In part II of this dissertation, we provide models of a realistic supply chain scheduling problem that capture both its combinatorial nature and its dependence on inventory availability. We present an extensive empirical evaluation of how well implementations of these models in commercially available software solve the problem. We are therefore able to address, within a specific problem, the need for scheduling to take into account related decision-making processes. In order to simultaneously deal with combinatorial and dynamic properties of real scheduling problems, in part III we propose to integrate queueing theory and deterministic scheduling. Firstly, by reviewing the queueing theory literature that deals with dynamic resource allocation and sequencing and outlining numerous future work directions, we build a strong foundation for the investigation of the integration of queueing theory and scheduling. Subsequently, we demonstrate that integration can take place on three levels: conceptual, theoretical and algorithmic. At the conceptual level, we combine concepts, ideas and problem settings from the two areas, showing that such combinations provide insights into the trade-off between long-run and short-run objectives. Next, we show that theoretical integration of queueing and scheduling can lead to long-run performance guarantees for scheduling algorithms that have previously been proved only for queueing policies. In particular, we are the first to prove, in two flow shop environments, the stability of a scheduling method that is based on the traditional scheduling literature and utilizes processing time information to make sequencing decisions. Finally, to address the algorithmic level of integration, we present, in an extensive future work chapter, one general approach for creating hybrid queueing/scheduling algorithms. To our knowledge, this dissertation is the first work that builds a framework for integrating queueing theory and scheduling. Motivated by characteristics of real problems, this dissertation takes a step toward extending scheduling research beyond traditional assumptions and addressing more realistic scheduling problems.

The central thesis of this dissertation is that by combining classical scheduling methodologies with those of inventory management and queueing theory we can better model, understand and solve complex real-world scheduling problems. In part II of this dissertation, we provide models of a realistic supply chain scheduling problem that capture both its combinatorial nature and its dependence on inventory availability. We present an extensive empirical evaluation of how well implementations of these models in commercially available software solve the problem. We are therefore able to address, within a specific problem, the need for scheduling to take into account related decision-making processes. In order to simultaneously deal with combinatorial and dynamic properties of real scheduling problems, in part III we propose to integrate queueing theory and deterministic scheduling. Firstly, by reviewing the queueing theory literature that deals with dynamic resource allocation and sequencing and outlining numerous future work directions, we build a strong foundation for the investigation of the integration of queueing theory and scheduling. Subsequently, we demonstrate that integration can take place on three levels: conceptual, theoretical and algorithmic. At the conceptual level, we combine concepts, ideas and problem settings from the two areas, showing that such combinations provide insights into the trade-off between long-run and short-run objectives. Next, we show that theoretical integration of queueing and scheduling can lead to long-run performance guarantees for scheduling algorithms that have previously been proved only for queueing policies. In particular, we are the first to prove, in two flow shop environments, the stability of a scheduling method that is based on the traditional scheduling literature and utilizes processing time information to make sequencing decisions. Finally, to address the algorithmic level of integration, we present, in an extensive future work chapter, one general approach for creating hybrid queueing/scheduling algorithms. To our knowledge, this dissertation is the first work that builds a framework for integrating queueing theory and scheduling. Motivated by characteristics of real problems, this dissertation takes a step toward extending scheduling research beyond traditional assumptions and addressing more realistic scheduling problems.

The fitting room is an important part of a clothing store, it's often where the customer decides if they want to buy the garment or not. Therefore it is important that the customer can feel safe and comfortable when they are trying the clothing. A typical fitting room in Sweden today has only one bright spotlight that emits light either towards the face or from the ceiling above. This study explores possible lighting solutions that take into account the customer's experience in the fitting room. The study aim to increase understanding of the importance of a good light in fitting rooms, so that customers gets a nice experience and that clothes, body shape and facial features are shown in a natural way. The issue therefore included how lighting can affect the customer's perception of the clothing and how the perception of body shape, facial features and the clothes change in different lighting solutions. To answer these questions, observations were made in various clothing stores, followed by an experimental study divided into two parts. The first part was a practical part where trying different lighting directions were tested on a mannequin, which resulted in three selected lighting solutions. The second part was a full-scale study. 15 people evaluated a fitting room with three different lighting solutions. The result demonstrates the importance of natural shadows and contrasts on the face and body and that it is important to consider how light falls and avoid glare. This is done by well-placed or shielded fixtures and by using several different lighting directions. The lighting in fitting rooms should be adapted to the type of clothes and customer group. / Provrummet är en viktig del i en klädbutik, det är ofta där kunden beslutar om plagget ska köpas eller inte. Det är därför viktigt att kunden kan känna sig trygg och bekväm vid klädprovningen. Ett typiskt provrum i Sverige idag har endast en ljuspunkt som belyser kunden antingen rakt framifrån eller ovanifrån. I denna studie undersöks tänkbara belysningslösningar som tar hänsyn till kundens upplevelse i provrummet. Studiens syfte var att öka förståelsen för hur viktigt det är med en god belysning i provrum, för att kunden ska få en bra upplevelse och att kläderna, kroppens form och anletsdrag ska framhävas på ett naturligt sätt. Frågeställningen innefattade därför hur belysningen kan påverka kundens upplevelse av klädprovningen och hur upplevelsen av kroppens form, anletsdrag och kläderna förändras i olika belysningslösningar. För att besvara dessa frågor gjordes observationer i olika klädbutiker, därefter genomfördes en experimentell studie som delades in i två delar. Första delen var en praktiskt prövande del där olika ljusriktningar testades på en skyltdocka. Denna resulterade i tre belysningslösningar att gå vidare med. Andra delen var en fullskalestudie där ett provrum byggdes upp med de tre olika belysningslösningar som sedan 15 stycken personer fick studera med hjälp av ett frågeformulär. Resultatet visar på vikten av att belysningen skapar naturliga skuggor och kontraster på kropp och ansikte, och att det är viktigt att tänka på hur ljuset faller, samt att belysningen inte är bländande. Detta görs genom välplacerade eller avskärmade armaturer och med flera olika ljusriktningar. Studien visar att belysningen i provrum bör anpassas efter typ av kläder och kundgrupp.