Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation

Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly

Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly

Traffic synchronization with controlled time of arrival for cost-efficient trajectories in high-density terminal airspace

The growth in air traffic has led to a continuously growing environmental sensitivity in aviation, encouraging the research into methods for achieving a greener air transportation. In this context, continuous descent operations (CDOs) allow aircraft to follow an optimum flight path that delivers major environmental and economic benefits, giving as a result engine-idle descents from the cruise altitude to right before landing that reduce fuel consumption, pollutant emissions and noise nuisance. However, this type of operations suffers from a well-known drawback: the loss of predictability from the air traffic control (ATC) point of view in terms of overfly times at the different waypoints of the route. In consequence, ATC requires large separation buffers, thus reducing the capacity of the airport. Previous works investigating this issue showed that the ability to meet a controlled time of arrival (CTA) at a metering fix could enable CDOs while simultaneously maintaining airport throughput. In this context, more research is needed focusing on how modern arrival managers (AMANs)—and extended arrival managers (E-AMANs)—could provide support to select the appropriate CTA. ATC would be in charge to provide the CTA to the pilot, who would then use four-dimensional (4D) flight management system (FMS) trajectory management capabilities to satisfy it. A key transformation to achieve a more efficient aircraft scheduling is the use of new air traffic management (ATM) paradigms, such as the trajectory based operations (TBO) concept. This concept aims at completely removing open-loop vectoring and strategic constraints on the trajectories by efficiently implementing a 4D trajectory negotiation process to synchronize airborne and ground equipment with the aim of maximizing both flight efficiency and throughput. The main objective of this PhD thesis is to develop methods to efficiently schedule arrival aircraft in terminal airspace, together with concepts of operations compliant with the TBO concept. The simulated arrival trajectories generated for all the experiments conducted in this PhD thesis, to the maximum possible extent, are considered to be energy-neutral CDOs, seeking to reduce the overall environmental impact of aircraft operations in the ATM system. Ultimately, the objective of this PhD is to achieve a more efficient arrival management of traffic, in which higher levels of predictability and similar levels of capacity are achieved, while the safety of the operations is kept. The designed experiments consider a TBO environment, involving a high synchronization between all the involved actors of the ATM system. Higher levels of automation and information sharing are expected, together with a modernization of both current ATC ground-support tools and aircraft FMSs to comply with the new TBO paradigm.L’increment de tràfic aeri ha portat a una major sensibilitat mediambiental en l’aviació, motivant la recerca en mètodes per aconseguir un transport aeri més ecològic. En aquest context, les operacions de descens continu (CDOs) permeten a les aeronaus seguir una trajectòria que aporta grans beneficis econòmics i ambientals, donant com a resultat descensos amb els motors al ralentí des de l’altitud de creuer fins just abans d’aterrar. Aquestes trajectòries redueixen el consum de combustible, les emissions contaminants i el soroll generat per les aeronaus. No obstant això, aquest tipus d’operacions té un gran desavantatge: la pèrdua de predictibilitat des del punt de vista del controlador aeri (ATC) en termes de temps de pas als diferents punts de la ruta. Com a conseqüència, l’ATC necessita assignar una major separació entre les aeronaus, la qual cosa comporta una reducció en la capacitat de l’aeroport. Estudis previs investigant aquest problema han demostrat que la capacitat de complir amb un temps controlat d’arribada (CTA) a un punt de la ruta (utilitzat per seqüenciar les aeronaus) podria habilitar les CDOs tot mantenint la capacitat de l’aeroport. En aquest context, es necessita investigar més en com els gestors d’arribades (AMANs) i els gestors d’arribades ampliats (E-AMANs) podrien donar suport en la selecció de la CTA més adequada. L’ATC seria l’encarregat d’enviar la CTA al pilot, el qual, per tal de complir amb la CTA, faria servir la capacitat de gestió de trajectòries d’un sistema de gestió de vol (FMS) de quatre dimensions (4D). Una transformació clau per aconseguir una gestió més eficient del tràfic d’arribada és l’ús de nous paradigmes de gestió del tràfic aeri (ATM), com per exemple el concepte d’operacions basades en trajectòries (TBO). Aquest concepte té com a objectiu eliminar completament de les trajectòries la vectorització en “bucle obert” i les restriccions estratègiques. Per aconseguir-ho, es proposa implementar de manera eficient una negociació de la trajectòria 4D, amb l’objectiu de sincronitzar l’equipament de terra amb el de l’aeronau, maximitzant d’aquesta manera l’eficiència dels vols i la capacitat del sistema. El principal objectiu d’aquest doctorat és desenvolupar mètodes per gestionar aeronaus de manera eficient en espai aeri terminal, juntament amb conceptes d’operacions que compleixin amb el concepte de TBO. Les trajectòries d’arribada simulades per tots els experiments definits en aquesta tesi doctoral, en la mesura que s’ha pogut, són CDOs d’energia neutral. D’aquesta manera, la idea és reduir el màxim possible l’impacte mediambiental de les operacions aèries al sistema ATM. En definitiva, l’objectiu d’aquest doctorat és aconseguir una gestió del tràfic d’arribada més eficient, obtenint una major predictibilitat i capacitat, i assegurant que la seguretat de les operacions es manté. Els experiments dissenyats consideren una situació on el concepte de TBO és present, el que comporta una sincronització elevada entre tots els actors implicats en el sistema ATM. Així mateix, s’esperen nivells majors d’automatització i de compartició d’informació, juntament amb una modernització de les eines de suport en terra a l’ATC i dels FMSs de les aeronaus, tot amb l’objectiu de complir amb el nou paradigma de TBO.El incremento de tráfico aéreo ha llevado a una mayor sensibilidad medioambiental en la aviación, motivando la investigación de métodos para conseguir un transporte aéreo más ecológico. En este contexto, las operaciones de descenso continuo (CDOs) permiten a las aeronaves seguir una trayectoria que aporta grandes beneficios económicos y ambientales, dando como resultado descensos con los motores al ralentí desde la altitud de crucero hasta justo antes de aterrizar. Estas trayectorias reducen el consumo de combustible, las emisiones contaminantes y el ruido generado por las aeronaves. No obstante, este tipo de operaciones tiene una gran desventaja: la pérdida de predictibilidad desde el punto de vista del controlador aéreo (ATC) en términos de tiempos de paso en los diferentes puntos de la ruta. Como consecuencia, el ATC necesita asignar una mayor separación entre las aeronaves, lo cual comporta una reducción en la capacidad del aeropuerto. Estudios previos investigando este problema han demostrado que la capacidad de cumplir con un tiempo controlado de llegada (CTA) en un punto de la ruta (utilizado para secuenciar las aeronaves) podría habilitar las CDOs manteniendo al mismo tiempo la capacidad del aeropuerto. En este contexto, es necesario investigar más en cómo los gestores de llegadas (AMANs)—y los gestores de llegadas extendidos (E-AMANs)—podrían dar soporte en la selección de la CTA más adecuada. El ATC sería el encargado de enviar la CTA al piloto, el cual, para cumplir con la CTA, usaría la capacidad de gestión de trayectorias de un sistema de gestión de vuelo (FMS) de cuatro dimensiones (4D). Una transformación clave para conseguir una gestión más eficiente del tráfico de llegada es el uso de nuevos paradigmas de gestión del tráfico aéreo (ATM), como por ejemplo el concepto de operaciones basadas en trayectorias (TBO). Este concepto tiene como objetivo eliminar completamente de las trayectorias la vectorización en “bucle abierto” y las restricciones estratégicas. Para conseguirlo, se propone implementar de manera eficiente una negociación de la trayectoria 4D, con el objetivo de sincronizar el equipamiento de tierra con el de la aeronave, maximizando de esta manera la eficiencia de los vuelos y la capacidad del sistema. El principal objetivo de este doctorado es desarrollar métodos para gestionar aeronaves de manera eficiente en espacio aéreo terminal, junto con conceptos de operaciones que cumplan con el concepto de TBO. Las trayectorias de llegada simuladas para todos los experimentos definidos en esta tesis doctoral, en la medida de lo posible, son CDOs de energía neutra. De esta manera, la idea es reducir lo máximo posible el impacto medioambiental de las operaciones aéreas en el sistema ATM. En definitiva, el objetivo de este doctorado es conseguir una gestión del tráfico de llegada más eficiente, obteniendo una mayor predictibilidad y capacidad, y asegurando que la seguridad de las operaciones se mantiene. Los experimentos diseñados consideran una situación xxi donde el concepto de TBO está presente, lo que comporta una sincronización elevada entre todos los actores implicados en el sistema ATM. Asimismo, se esperan mayores niveles de automatización y de compartición de información, junto con una modernización de las herramientas de soporte en tierra al ATC y de los FMSs de las aeronaves, todo con el objetivo de cumplir con el nuevo paradigma de TBO. Primero de todo, se define un marco para la optimización de trayectorias utilizado para generar las trayectorias simuladas para los experimentos definidos en esta tesis doctoral. A continuación, se evalúan los beneficios de volar CDOs de energía neutra comparándolas con trayectorias reales obtenidas de datos de vuelo históricos. Se comparan dos fuentes de datos, concluyendo cuál es la más adecuada para estudios de eficiencia en espacio aéreo terminal. Las CDOs de energía neutra son el tipo preferido de trayectorias desde un punto de vista medioambiental pero, dependiendo de la cantidad de tráfico, podría ser imposible para el ATC asignar una CTA que pueda ser cumplida por las aeronaves mientras vuelan la ruta de llegada publicada. En esta tesis doctoral, se comparan dos estrategias con el objetivo de cumplir con la CTA asignada: volar CDOs de energía neutra por rutas más largas/cortas o volar descensos con el motor accionado por la ruta publicada. Para ambas estrategias, se analiza la sensibilidad del consumo de combustible a diferentes parámetros, como la altitud inicial de crucero o la velocidad del viento. Finalmente, en esta tesis doctoral se analizan dos estrategias para gestionar de manera eficiente el tráfico de llegada en espacio aéreo terminal. Primero, se utiliza una estrategia provisional a medio camino entre la negociación completa de trayectorias 4D y la vectorización en “bucle abierto”: se propone una metodología para gestionar de manera eficaz tráfico de llegada donde las aeronaves vuelan CDOs de energía neutra en un procedimiento de navegación de área (RNAV) conocido como trombón. A continuación, se propone una nueva metodología para generar rutas de llegada dinámicas que se adaptan automáticamente a la demanda actual de tráfico. De igual manera, se aplican CDOs de energía neutra a todo el tráfico de llegada. Hay diferentes factores a considerar que podrían limitar los beneficios de las soluciones propuestas. La cantidad y distribución del tráfico de llegada tiene un gran efecto sobre los resultados obtenidos, limitando en algunos casos una gestión eficiente de las aeronaves de llegada. Además, algunas de las soluciones propuestas comportan elevadas cargas computacionales que podrían limitar su aplicación operacional, motivando mayor investigación en el futuro con el fin de optimizar los modelos y metodologías utilizados. Finalmente, permitir a algunos aviones volar descensos con el motor accionado podría facilitar la gestión de las aeronaves de llegada en los experimentos que se centran en el procedimiento de trombón y en la generación de rutas de llegada dinámicas.Postprint (published version

A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems

[EN] The urgent need for sustainable development is imposing radical changes in the way manufacturing systems are designed and implemented. The overall sustainability in industrial activities of manufacturing companies must be achieved at the same time that they face unprecedented levels of global competition. Therefore, there is a well-known need for tools and methods that can support the design and implementation of these systems in an effective way. This paper proposes an engineering method that helps researchers to design sustainable intelligent manufacturing systems. The approach is focused on the identification of the manufacturing components and the design and integration of sustainability-oriented mechanisms in the system specification, providing specific development guidelines and tools with built-in support for sustainable features. Besides, a set of case studies is presented in order to assess the proposed method.This research was supported by research projects TIN2015-65515-C4-1-R and TIN2016-80856-R from the Spanish government. The authors would like to acknowledge T. Bonte for her contribution to the NetLogo simulator of the AIP PRIMECA cell.Giret Boggino, AS.; Trentesaux, D.; Salido Gregorio, MÁ.; Garcia, E.; Adam, E. (2017). A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems. Journal of Cleaner Production. 167(1):1370-1386. https://doi.org/10.1016/j.jclepro.2017.03.079S13701386167

Time and Energy Managed Operations (TEMO): Cessna Citation II Flight Trials

From 9-26 October 2015 the Netherlands Aerospace Centre (NLR) in cooperation with Delft University of Technology (DUT) has executed Clean Sky flight trials with the Cessna Citation II research aircraft. The trials consisted of several descents and approaches at the Eelde airport near Groningen, demonstrating the TEMO (Time and Energy Managed Operations) concept developed in the Clean Sky Joint Technology Initiative research programme as part of the Systems for Green Operations (SGO) Integrated Technology Demonstrator. A TEMO descent aims to achieve an energy-managed idle-thrust continuous descent operation (CDO) while satisfying ATC time constraints, to maintain runway throughput. An optimal descent plan is calculated with an advanced on-board real-time aircraft trajectory optimisation algorithm considering forecasted weather and aircraft performance. The optimised descent plan was executed using the speed-on-elevator mode of an experimental Fly-By-Wire (FBW) system connected to the pitch servo motor of the Cessna Citation II aircraft. Several TEMO conceptual variants have been flown. It has been demonstrated that the TEMO concept enables arrival with timing errors below 10 seconds. The project was realised with the support of CONCORDE partners Universitat Politècnica de Catalunya (UPC) and PildoLabs from Barcelona, and the Royal Netherlands Meteorological Institute (KNMI).Peer ReviewedPostprint (published version

Flight testing Time and Energy Managed Operations (TEMO)

The expected growth in air traffic combined with an increased public concern for the environment, have forced legislators to rethink the current air traffic system design. The current air traffic system operates at its capacity limits and is expected to lead to increased delays if traffic levels grow even further. Both in the United States and Europe, research projects have been initiated to develop the future Air Transportation System (ATS) to address capacity, and environmental, safety and economic issues. To address the environmental issues during descent and approach, a novel Continuous Descent Operations (CDO) concept, named Time and Energy Managed Operations (TEMO), has been developed co-sponsored by the Clean Sky Joint Undertaking. It uses energy principles to reduce fuel burn, gaseous emissions and noise nuisance whilst maintaining runway capacity. Different from other CDO concepts, TEMO optimizes the descent by using energy management to achieve a continuous engine-idle descent, while satisfying time constraints on both the Initial Approach Fix (IAF) and the runway threshold. As such, TEMO uses timemetering at two control points to facilitate flow management and arrival spacing. TEMO is in line with SESAR step 2 capabilities, since it proposes 4D trajectory management and is aimed at providing significant environmental benefits in the arrival phase without negatively affecting throughput, even in high density and peak-hour operations. In particular, TEMO addresses SESAR operational improvement (OI) TS-103: Controlled Time of Arrival (CTA) through use of datalink [1]. TEMO has been validated starting from initial performance batch studies at Technology Readiness Level (TRL) 3, up to Human-in-the-Loop studies in realistic environments using a moving base flight simulator at TRL 5 ([2]-[6]). In this paper the definition, preparation, performance and analysis of a flight test experiment is described with the objective to demonstrate the ability of the TEMO algorithm to provide accurate and safe aircraft guidance toward the Initial Approach Fix (IAF), and further down to the Stabilization Point (1000 ft AGL), to demonstrate the ability of the TEMO algorithm to meet absolute time requirements at IAF and/or runway threshold and to evaluate the performance of the system under test (e.g. fuel usage).Peer ReviewedPostprint (published version

A multiobjective evolutionary algorithm for achieving energy efficiency in production environments integrated with multiple automated guided vehicles

Increasing energy shortages and environmental pollution have made energy efficiency an urgent concern in manufacturing plants. Most studies looking into sustainable production in general and energy-efficient production scheduling in particular, however, have not paid much attention to logistical factors (e.g., transport and setup). This study integrates multiple automated guided vehicles (AGVs) into a job-shop environment. We propose a multiobjective scheduling model that considers machine processing, sequence-dependent setup and AGV transport, aiming to simultaneously minimize the makespan, total idle time of machines and total energy consumption of both machines and AGVs. To solve this problem, an effective multiobjective evolutionary algorithm (EMOEA) is developed. Within the EMOEA, an efficient encoding/decoding method is designed to represent and decode each solution. A new crossover operator is proposed for AGV assignment and AGV speed sequences. To balance the exploration and exploitation ability of the EMOEA, an opposition-based learning strategy is incorporated. A total of 75 benchmark instances and a real-world case are used for our experimental study. Taguchi analysis is applied to determine the best combination of key parameters for the EMOEA. Extensive computational experiments show that properly increasing the number of AGVs can shorten the waiting time of machines and achieve a balance between economic and environmental objectives for production systems. The experimental results confirm that the proposed EMOEA is significantly better at solving the problem than three other well-known algorithms. Our findings here have significant managerial implications for real-world manufacturing environments integrated with AGVs

Federated Robust Embedded Systems: Concepts and Challenges

The development within the area of embedded systems (ESs) is moving rapidly, not least due to falling costs of computation and communication equipment. It is believed that increased communication opportunities will lead to the future ESs no longer being parts of isolated products, but rather parts of larger communities or federations of ESs, within which information is exchanged for the benefit of all participants. This vision is asserted by a number of interrelated research topics, such as the internet of things, cyber-physical systems, systems of systems, and multi-agent systems. In this work, the focus is primarily on ESs, with their specific real-time and safety requirements. While the vision of interconnected ESs is quite promising, it also brings great challenges to the development of future systems in an efficient, safe, and reliable way. In this work, a pre-study has been carried out in order to gain a better understanding about common concepts and challenges that naturally arise in federations of ESs. The work was organized around a series of workshops, with contributions from both academic participants and industrial partners with a strong experience in ES development. During the workshops, a portfolio of possible ES federation scenarios was collected, and a number of application examples were discussed more thoroughly on different abstraction levels, starting from screening the nature of interactions on the federation level and proceeding down to the implementation details within each ES. These discussions led to a better understanding of what can be expected in the future federated ESs. In this report, the discussed applications are summarized, together with their characteristics, challenges, and necessary solution elements, providing a ground for the future research within the area of communicating ESs

A Genetic-Algorithm-Based Approach for Optimizing Tool Utilization and Makespan in FMS Scheduling

This paper proposes a genetic algorithm approach to solve the identical parallel machines problem with tooling constraints in job shop flexible manufacturing systems (JS-FMSs) with the consideration of tool wear. The approach takes into account the residual useful life of tools and allocates a set of jobs with specific processing times and tooling requirements on identical parallel machines. Two metrics are introduced to evaluate the scheduling decisions and optimize the scheduling process, with the competitive goal of maximizing tool utilization and minimizing production makespan. The proposed approach searches for a set of optimal solutions on the Pareto front that offers the best possible balance between these two objectives, achieving optimal local performance in terms of both makespan and tool utilization. The approach is implemented with a customized genetic algorithm and validated on a real case study from a company operating in the aerospace sector, which confirms its effectiveness in increasing tool utilization and reducing the makespan. The results show that the proposed approach has significant practical implications for the manufacturing industry, particularly in the production of high-value materials such as those in the aerospace sector that require costly tools. This paper contributes to the operational research community by providing advanced scheduling algorithms that can optimize both the makespan and the tool utilization concurrently, improving production efficiency and maintaining competitiveness in the manufacturing industry