A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Integrating Analysis Into a Warehouse Design Workflow

Supply chain analyses, including those related to material handling systems, are typically purpose-built to answer specific questions and therefore have many different implementations depending on the question, the instance data, and the solver. The purpose-built nature of these models makes it difficult to integrate them into an iterative design workflow. Despite the myriad analysis implementations, the fundamental structure of these systems and their problem domain remains unchanged, suggesting that perhaps analyses could be automatically generated on demand, given an appropriate specification of the particular system to be analyzed. We apply model-based systems engineering (MBSE) methodologies to explore this possibility in the context of functional warehouse design

A petri-net based methodology for modeling, simulation, and control of flexible manufacturing systems

Global competition has made it necessary for manufacturers to introduce such advanced technologies as flexible and agile manufacturing, intelligent automation, and computer-integrated manufacturing. However, the application extent of these technologies varies from industry to industry and has met various degrees of success. One critical barrier leading to successful implementation of advanced manufacturing systems is the ever-increasing complexity in their modeling, analysis, simulation, and control. The purpose of this work is to introduce a set of Petri net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs). More specifically, this work proposes Petri nets as an integrated tool for modeling, simulation, and control of flexible manufacturing systems (FMSs). The contributions of this work are multifold. First, it demonstrates a new application of PNs for simulation by evaluating the performance of pull and push diagrams in manufacturing systems. Second, it introduces a class of PNs, Augmented-timed Petri nets (ATPNs) in order to increase the power of PNs to simulate and control flexible systems with breakdowns. Third, it proposes a new class of PNs called Realtime Petri nets (RTPNs) for discrete event control of FMS s. The detailed comparison between RTPNs and traditional discrete event methods such as ladder logic diagrams is presented to answer the basic question \u27Why is a PN better tool than ladder logic diagram?\u27 and to justify the PN method. Also, a conversion procedure that automatically generates PN models from a given class of logic control specifications is presented. Finally, a methodology that uses PNs for the development of object-oriented control software is proposed. The present work extends the PN state-of-the-art in two ways. First, it offers a wide scope for engineers and managers who are responsible for the design and the implementation of modem manufacturing systems to evaluate Petri nets for applications in their work. Second, it further develops Petri net-based methods for discrete event control of manufacturing systems

TAO Conceptual Design Report: A Precision Measurement of the Reactor Antineutrino Spectrum with Sub-percent Energy Resolution

The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the Taishan Nuclear Power Plant. The reactor antineutrino spectrum will be measured with sub-percent energy resolution, to provide a reference spectrum for future reactor neutrino experiments, and to provide a benchmark measurement to test nuclear databases. A spherical acrylic vessel containing 2.8 ton gadolinium-doped liquid scintillator will be viewed by 10 m^2 Silicon Photomultipliers (SiPMs) of >50% photon detection efficiency with almost full coverage. The photoelectron yield is about 4500 per MeV, an order higher than any existing large-scale liquid scintillator detectors. The detector operates at -50 degree C to lower the dark noise of SiPMs to an acceptable level. The detector will measure about 2000 reactor antineutrinos per day, and is designed to be well shielded from cosmogenic backgrounds and ambient radioactivities to have about 10% background-to-signal ratio. The experiment is expected to start operation in 2022

Scheduling and discrete event control of flexible manufacturing systems based on Petri nets

A flexible manufacturing system (FMS) is a computerized production system that can simultaneously manufacture multiple types of products using various resources such as robots and multi-purpose machines. The central problems associated with design of flexible manufacturing systems are related to process planning, scheduling, coordination control, and monitoring. Many methods exist for scheduling and control of flexible manufacturing systems, although very few methods have addressed the complexity of whole FMS operations. This thesis presents a Petri net based method for deadlock-free scheduling and discrete event control of flexible manufacturing systems. A significant advantage of Petri net based methods is their powerful modeling capability. Petri nets can explicitly and concisely model the concurrent and asynchronous activities, multi-layer resource sharing, routing flexibility, limited buffers and precedence constraints in FMSs. Petri nets can also provide an explicit way for considering deadlock situations in FMSs, and thus facilitate significantly the design of a deadlock-free scheduling and control system. The contributions of this work are multifold. First, it develops a methodology for discrete event controller synthesis for flexible manufacturing systems in a timed Petri net framework. The resulting Petri nets have the desired qualitative properties of liveness, boundedness (safeness), and reversibility, which imply freedom from deadlock, no capacity overflow, and cyclic behavior, respectively. This precludes the costly mathematical analysis for these properties and reduces on-line computation overhead to avoid deadlocks. The performance and sensitivity of resulting Petri nets, thus corresponding control systems, are evaluated. Second, it introduces a hybrid heuristic search algorithm based on Petri nets for deadlock-free scheduling of flexible manufacturing systems. The issues such as deadlock, routing flexibility, multiple lot size, limited buffer size and material handling (loading/unloading) are explored. Third, it proposes a way to employ fuzzy dispatching rules in a Petri net framework for multi-criterion scheduling. Finally, it shows the effectiveness of the developed methods through several manufacturing system examples compared with benchmark dispatching rules, integer programming and Lagrangian relaxation approaches

Strategies for dynamic appointment making by container terminals

We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much

Feasibility study of an Integrated Program for Aerospace vehicle Design (IPAD). Volume 2: The design process

The extent to which IPAD is to support the design process is identified. Case studies of representative aerospace products were developed as models to characterize the design process and to provide design requirements for the IPAD computing system

Petri net approaches for modeling, controlling, and validating flexible manufacturing systems

In this dissertation, we introduce the fundamental ideas and constructs of Petri net models such as ordinary, timed, colored, stochastic, control, and neural, and present some studies that emphasize Petri nets theories and applications as extended research fields that provide suitable platforms in modeling, controlling, validating, and evaluating concurrent systems, information systems, and a versatile dynamic system and manufacturing systems;We then suggest some of extensions that help make Petri nets useful for modeling and analyzing discrete event systems and manufacturing systems models based on the context of a versatile manufacturing system, and applies extended Petri nets models to several manufacturing systems such as an assembly cell, an Automated Palletized Conveyor System, and a tooling machine to show increased modeling power and efficient analysis methods;Finally, Validation methods are presented for these models and results of a performance analysis from a deterministic and stochastic model are used to reorganize and re-evaluate a manufacturing system in order to increase its flexibility

DES Configurators for Rapid Virtual Prototyping and Optimisation of Manufacturing Systems

In the framework of the COPERNICO research project configurators were developed under the Siemens Tecnomatix Plant Simulation software environment, which support the rapid creation of the discrete event simulation (DES) models of several types of manufacturing systems. With the use of the configurators after defining the required input data – such as the product mix, production processes, layout prototype, etc. – the DES models of the manufacturing system alternatives will be automatically created. The layout prototypes are based on a cladistics classification of manufacturing systems. The aim of the configurators is not only to purely create the simulation models but also to create models that can be used for further optimisations, that can be done e.g. by using the built in genetic algorithms tool, based on specific objectives. In this paper some research results are demonstrated on how the configurators create DES models and how the models can be applied

Maximum Entropy/Optimal Projection (MEOP) control design synthesis: Optimal quantification of the major design tradeoffs

The underlying philosophy and motivation of the optimal projection/maximum entropy (OP/ME) stochastic modeling and reduced control design methodology for high order systems with parameter uncertainties are discussed. The OP/ME design equations for reduced-order dynamic compensation including the effect of parameter uncertainties are reviewed. The application of the methodology to several Large Space Structures (LSS) problems of representative complexity is illustrated