Hybrid Dynamical Approach Makes FMS Scheduling More Effective

In the present paper a general job-shop type scheduling problem for FMS is considered. About ten years ago by paper Perkins, Kumar [3] a new direction, the use of hybrid dynamical approach to the solution of manufacturing scheduling problems arose. Recently, Matveev, Savkin [5] developed a qualitative theory for the investigation of these and similar problems. In the present paper an attempt is made to show the place and way of use of this approach in the solution of industrial problems. The formulation of the tasks involves complex problem obtained by CAPP and PPS subsystems interaction of CIM systems. The effect of the use of hybrid dynamical approach is in the opportunity of overlapping production, which may result in a significant increase of efficiency of equipment utilization. A proposal is given to determine the so called demand rates which are ideal inputs of servers (machines) realizing production according to the orders of higher hierarchical levels of PPS. The use of hybrid dynamical approach can be well investigated for single- machine (server) processing of multiple flows. But, at an ideal flow at the input of the machines (servers) the outputs differ from the ideal input for the next machines in order. This gives difficulties for job-shop type processing. A proposal is given in the paper to overcome this difficulty by the use of controlled buffers proposed. As far as we know, this is the first publication in Hungary dealing with the use of hybrid dynamical approach to FMS scheduling

Optimizing Time Utilization of FMS

The aim of the research is to solve the problem of simultaneous production on the flexible manufacturing system with different combination of product types and quantities that will give maximal utilization of production system. The presumption for good utilization of FMS (Flexible Manufacturing System) is in forming of working order with such product type structure that will make possible of production processing with minimal time load of complete production system. Working order structure from the point of product types and quantities is dictated by market demands that are known earlier. Because the structure of particular working order is not harmonized with the exploitation characteristics of FMS, we are faced with problem how to realize working order in such conditions as well as how to achieve main goal: shorter machining cycle with less time occupation of production system. The method based on two phases for solving problem of control working order realization is presented in the work. In the first phase the selection of optimal combination of process plans which gives minimal time load of production system through simultaneous production of different products and their quantities is given. In the second phase the order of part production and the order of particular operations processing is optimized. The optimization problem in both phases of control is solved by application of genetic algorithm approach. The software for computing and optimizing of processing order on FMS is developed

Optimal control based method for design and analysis of continuous descent arrivals

Continuous Descent Arrival (CDA) is a procedure where aircraft descend, at or near idle thrust, from their cruise altitude to their Final Approach Fix without leveling off. By eliminating inefficient leveling off at low altitude, CDA provides benefits such as fuel savings, flight time savings, and the significant noise reduction near airports, but the usage of CDAs has been limited in low traffic condition due to difficulty in the separation management. For the successful CDA without degradation of the runway throughput, air traffic controllers should know the performance bound of the CDA trajectory and control the time of arrival for each aircraft, which is interpreted as Required Time of Arrival (RTA) from the aircraft standpoint. This thesis proposes a novel trajectory optimization methodology to meet RTA constraint. The CDA trajectory optimization problem in the flight management system is modeled as a path constrained optimal control problem of switched dynamical system. A sequential method that performs mode sequence estimation and parameter optimization, sequentially, is proposed to solve this problem. By analyzing the relaxed optimal solution with simplified dynamics, a computationally efficient algorithm to find the optimal switching structure is proposed and applied for the mode sequence estimation. This thesis also proposes a performance-bound analysis methodology using optimal control techniques to help controllers make a feasible schedule for CDA operations at a meter fix. The feasible time range analysis for a wide variety of aircraft is performed by using the proposed methodology. Based on the analysis result, a single flight time strategy is proposed for the application of CDA in high traffic conditions. The simulation with real traffic data has been shown that the single flight time strategy, combined with the proposed fixed RTA trajectory optimization, guarantees the conflict free CDA operation.Ph.D

Strategies for including cloud-computing into an engineering modeling workflow

With the advent of cloud computing, high-end computing, networking, and storage resources are available on-demand at a relatively low price point. Internet applications in the consumer and increasingly in the enterprise space are making use of these resources to upgrade existing applications and build new ones. This is made possible by building decentralized applications that can be integrated with one another through web-enabled application programming interfaces (APIs). However, in the fields of engineering and computational science, cloud computing resources have been utilized primarily to augment existing high-performance computing hardware, but engineering model integrations still occur by the use of software libraries. In this research, a novel approach is proposed where engineering models are constructed as independent services that publish web-enabled APIs. To enable this, the engineering models are built as stateless microservices that solve a single computational problem. Composite services are then built utilizing these independent component models, much like in the consumer application space. Interactions between component models is orchestrated by a federation management system. This proposed approach is then demonstrated by disaggregating an existing monolithic model for a cookstove into a set of component models. The component models are then reintegrated and compared with the original model for computational accuracy and run-time. Additionally, a novel engineering workflow is proposed that reuses computational data by constructing reduced-order models (ROMs). This framework is evaluated empirically for a number of producers and consumers of engineering models based on computation and data synchronization aspects. The framework is also evaluated by simulating an engineering design workflow with multiple producers and consumers at various stages during the design process. Finally, concepts from the federated system of models and ROMs are combined to propose the concept of a hybrid model (information artefact). The hybrid model is a web-enabled microservice that encapsulates information from multiple engineering models at varying fidelities, and responds to queries based on the best available information. Rules for the construction of hybrid models have been proposed and evaluated in the context of engineering workflows

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of automation were proposed for integrated flight planning and re-routing functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is provided. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, airspace and airport operations

Optimization of job shop scheduling with material handling by automated guided vehicle

Job Shop Scheduling with Material Handling has attracted increasing attention in both industry and academia, especially with the inception of Industry 4.0 and smart manufacturing. A smart manufacturing system calls for efficient and effective production planning. On a typical modern shop floor, jobs of various types follow certain processing routes through machines or work centers, and automated guided vehicles (AGVs) are utilized to handle the jobs. In this research, the optimization of a shop floor with AGV is carried out, and we also consider the planning scenario under variable processing time of jobs. The goal is to minimize the shop floor production makespan or other specific criteria correlated with makespan, by scheduling the operations of job processing and routing the AGVs. This dissertation includes three research studies that will constitute my doctoral work. In the first study, we discuss a simplified case in which the scheduling problem is reformulated into a vehicle dispatching (assignment) problem. A few AGV dispatching strategies are proposed based on the deterministic optimization of network assignment problems. The AGV dispatching strategies take future transportation requests into consideration and optimally configure transportation resources such that material handling can be more efficient than those adopting classic AGV assignment rules in which only the current request is considered. The strategies are demonstrated and validated with a case study based on a shop floor in literature and compared to classic AGV assignment rules. The results show that AGV dispatching with adoption of the proposed strategy has better performance on some specific criterions like minimizing job waiting time. In the second study, an efficient heuristic algorithm for classic Job Shop Scheduling with Material Handling is proposed. Typically, the job shop scheduling problem and material handling problem are studied separately due to the complexity of both problems. However, considering these two types of decisions in the same model offers benefits since the decisions are related to each other. In this research, we aim to study the scheduling of job operations together with the AGV routing/scheduling, and a formulation as well as solution techniques are proposed. The proposed heuristic algorithm starts from an optimal job shop scheduling solution without limiting the size of AGV fleet, and iteratively reduces the number of available vehicles until the fleet size is equal to the original requirements. The computational experiments suggest that compared to existing solution techniques in literature, the proposed algorithm can achieve comparable solution quality on makespan with much higher computational efficiency. In the third study, we take the variability of processing time into consideration in optimizing job shop scheduling with material handling. Variability caused by random effects and deterioration is discussed, and a series of models are developed to accommodate random and deteriorating processing time respectively. With random processing time, the model is formulated as a Stochastic Programming Job Shop Scheduling with Material Handling model, and with deteriorating processing time the model can be nonlinear under specific deteriorating functions. Based on a widely adopted dataset in existing literature, the stochastic programming model were solved with Pyomo, and models with deterioration were linearized and solved with CPLEX. By considering variable processing time, the JSSMH models can better adapt to real production scenarios

ZASTOSOWANIE SIECI PETRIEGO W SYSTEMACH WSPOMAGANIA DECYZJI OPARTYCH NA INTELIGENTNEJ WIELOŹRÓDŁOWEJ ANALIZIE DANYCH

The paper deals with the design of data analysis systems for business process automation. A general scheme of decision support system was developed in which one of the modules is based on Petri Nets. The way of implementation of Petri Net model in optimization problem regarding service-oriented decision support system was shown. The Petri Net model of distribution workflow was presented and simulation experiments was completed. As a result the optimal solution as a set of parameters was emerged.Artykuł dotyczy problematyki projektowania zautomatyzowanych systemów analizy danych biznesowych. Opracowano ogólny model systemu wspomagania decyzji, w którym jeden z modułów funkcjonuje w oparciu o sieci Petriego. Zaprezentowano sposób implementacji sieci Petriego do realizacji zadań optymalizacyjnych dotyczących zorientowanego na usługi systemu wspomagania decyzji. Przeprowadzono szereg eksperymentów symulacyjnych wykorzystując model przepływu pracy utworzony na bazie sieci Petriego. Rezultatem badań było wyłonienie optymalnego zbioru parametrów procesu biznesowego