CRAFT: Comprehensive Resilience Assessment Framework for Transportation Systems in Urban Areas

Urban areas in the US and around the globe are facing increasingly complex resilience challenges. Among the components of the “urban system,” transportation networks are among the most critical facilitators that support the lives, interactions, and dynamics of urban dwellers. They are essential to the well-being of the society not only under business-as-usual conditions, but also during times of disaster for the entire response and recovery timeline. This paper introduces CRAFT (Comprehensive Resilience Assessment Framework for Transportation Systems in Urban Areas), which is designed to achieve holistic analyses of transportation disruptions by addressing the many shortcomings and research gaps in this domain. The framework couples a novel structure-specific modeling methodology with a high-fidelity metropolis-scale travel demand model based on real socioeconomic data, and produces results, which, in turn, serve as input for a state-of-the-art socioeconomic impact analysis methodology that is based on computable general equilibrium (CGE) analysis. By the virtues of its data-intensive, model-based, and cross-disciplinary nature, CRAFT aims to capture and incorporate many details that are usually neglected in traditional approaches, and generates resilience insights at 3 levels: (1) system component level (e.g., damages to bridges, tunnels and information on component recovery), (2) system level (e.g., road network disruptions, reconfiguration of traffic and network level functionality) and (3) regional economic level (e.g., impacts on regional GDP, employment, economic resilience). The objective of this paper is to introduce CRAFT and to demonstrate the workings of its first coupling between the hazard and transportation modules through a case study on the Greater Los Angeles Area.     

Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.     

A CAD-Based hierarchical approach to interference detection among fixture modules in a reconfigurable fixturing system

A reconfigurable fixturing system has been developed for a computer-integrated assembly environment. The fixturing system employs a number of fixture modules which are set-up, adjusted and changed automatically by the assembly robot. A dedicated software program has been developed for the design, analysis, and verification of the fixture layout. The software program has been integrated with a commercially available computer-aided design (CAD) package to provide a user-friendly platform for modeling and display purposes. The robot program for setting up, adjusting, and dismantling the designed fixture is generated automatically. Interference between fixture modules during the fixture construction may arise due to incorrect selection of the fixture contact points at the design stage. The objective of the work described here is to develop a hierarchical approach for calculation of interference between fixture modules in a reconfigurable fixturing system. The formulation for the interference detection employs geometrical constraints as the basis. The approach does not require detailed simulation of the fixture construction for interference detection.     

Assembly line balancing under uncertainty: Robust optimization models and exact solution method

This research deals with line balancing under uncertainty and presents two robust optimization models. Interval uncertainty for operation times was assumed. The methods proposed generate line designs that are protected against this type of disruptions. A decomposition based algorithm was developed and combined with enhancement strategies to solve optimally large scale instances. The efficiency of this algorithm was tested and the experimental results were presented. The theoretical contribution of this paper lies in the novel models proposed and the decomposition based exact algorithm developed. Moreover, it is of practical interest since the production rate of the assembly lines designed with our algorithm will be more reliable as uncertainty is incorporated. Furthermore, this is a pioneering work on robust assembly line balancing and should serve as the basis for a decision support system on this subject.     

A digital twin-driven human-robot collaborative assembly approach in the wake of COVID-19

In the wake of COVID-19, the production demand of medical equipment is increasing rapidly. This type of products is mainly assembled by hand or fixed program with complex and flexible structure. However, the low efficiency and adaptability in current assembly mode are unable to meet the assembly requirements. So in this paper, a new framework of human-robot collaborative (HRC) assembly based on digital twin (DT) is proposed. The data management system of proposed framework integrates all kinds of data from digital twin spaces. In order to obtain the HRC strategy and action sequence in dynamic environment, the double deep deterministic policy gradient (D-DDPG) is applied as optimization model in DT. During assembly, the performance model is adopted to evaluate the quality of resilience assembly. The proposed framework is finally validated by an alternator assembly case, which proves that DT-based HRC assembly has a significant effect on improving assembly efficiency and safety.     

Performance optimization of integrated job-driven and resilience factors by means of a quantitative approach

Job-driven factors affect overall productivity and describe the characteristics influencing human performance. Resilience engineering (RE) is the capability of systems and groups to cope with disturbances and disruptions to enhance their performance. This study employs data envelopment analysis (DEA) approach to optimize the overall performance of a ceramic tile company by considering resilience and job-driven factors. The required data were collected via a standard questionnaire whose reliability was examined by statistical methods. In this regard, sensitivity analysis was performed to determine the most important factors. DEA results showed that job stress, job burnout, and management commitment play a central role in the investigated system. The overall results indicated that job-driven factors have a higher weight than resilience factors. This is one of the first studies that concurrently examine job-driven and resilience factors. Second, the present study uses DEA method in a ceramic tile manufacturer to achieve optimum performance. Third, the weights of all factors are computed for optimum redesign and re-engineering. Fourth, decision-makers may identify weak areas and strong points of their systems with respect to job-driven and resilience factors.     

Modelling and control of an assembly/disassembly mechatronics line served by mobile robot with manipulator

The aim of this paper is to reverse an assembly line using a mobile platform equipped with a manipulator. By reversibility we mean that the line is able to perform disassembly. For this purpose, an assembly/disassembly line balancing (A/DLB) and a synchronised hybrid Petri nets (SHPN) model will be used to model and control an assembly/disassembly mechatronics line (A/DML), with a fixed number of workstations, served by a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM). The SHPN model is a hybrid type, where A/DML is the discrete part, and WMR with RM is the continuous part. Moreover, the model operates in synchronised mode with signals from sensors. Disassembly starts after the assembly process and after the assembled piece fails the quality test, in order to recover the parts. The WMR with RM is used only during disassembly, to transport the parts from the disassembling locations to the storage locations. Using these models and a LabView platform, a real-time control structure has been designed and implemented, allowing automated assembly and disassembly, where the latter is assisted by a mobile platform equipped with a manipulator.     

Synchronization-oriented reconfiguration of FPAI under graduation intelligent manufacturing system in the COVID-19 pandemic and beyond

Companies with manufacturing systems that are more responsive and resilient will be able to survive or even gain market shares in the face of the unpredicted variable of an outbreak similar to the COVID-19 pandemic. Motivated by an industrial company restructuring its manufacturing system with the layout of fixed-position assembly islands (FPAI) during the COVID-19 pandemic, this paper introduces the synchronization-oriented reconfiguration of FPAI under Graduation Intelligent Manufacturing System (GiMS). Inspired by the graduation ceremony, a novel manufacturing mode-Graduation Manufacturing System (GMS) with ticket-based reconfigurable structures, is designed for organizing production operations with simplicity and resilience for the layout of FPAI. The IIoT and digital twin-enabled GiMS is developed for transforming real-time visibility in operations to support the reconfiguration of the manufacturing system. A synchronization-oriented reconfiguration mechanism is proposed to achieve the synchronous interaction among changing customer demand, island configuration, and production activities allocation rapidly and cost-effectively. Cloud services integrating the proposed reconfiguration mechanism are developed for managers and onsite operators for supporting the successful reconfiguration implementation with enhanced operational visibility. Through the case study of an industrial company, the effectiveness of the proposed concept and approach is verified.     

Revision and validation of the Connor-Davidson Resilience Scale of coal miners in China

The psychological state of coal miners may have negative changes because of the long-term underground working environment and complex production process and will cause unsafe behaviour. Resilience can enhance the adaptability of individuals to high-risk and high-pressure environments and predict unsafe behaviour. However, currently little research has been done to develop resilience measuring tools for coal miners. Therefore, this paper revised and verified the Connor-Davidson Resilience Scale (CD-RISC) among coal miners in China and developed an individual resilience scale available for the coal industry. Five hundred and twenty subject coal miners have finished the initial test, and the exploratory factor analysis and reliability analysis were used to revise the CD-RISC. Another survey on 639 samples was then conducted to assess a confirmatory factor analysis and test-retest reliability of the resilience scale. The resulting scale has two dimensions, tenacity and strength, including a collection of 6 items. This study assists in further exploring the structural factor of individual resilience level for China coal industry, and provides a new research idea for occupational health, and contributes to the safety management and sustainable development of the coal enterprises.     

A study on production line automation with LonWorks™ control networks

Industrial automation systems look forward to implement new generation of control architecture in response to high flexibility and productivity. Control system users are now keen to promote the emergence of digital technology (DT) in place of 4–20-mA analogue systems. The trend is to implement DT-based distributed control systems (DCS) solution. DCS is becoming very popular because of its own advantages over the whole operating system. A case study in the context of realizing production line automation with DT and DCS philosophy has been presented in this paper. Emphasis has been given on the use of “Fieldbus technology: a digital control networking system”. In this study, Echelon's Local Operating Network (LON) fieldbus system was used because of availability of a wide range of products. A system was integrated with sensors, microswitches and a drive, while a pick-and-place robotic workstation was selected as the representative target platform.     

A general framework for assessing system resilience using Bayesian networks: A case study of sulfuric acid manufacturer

Supply chains play an important role in modern society and national economic development. In recent years, supply chains are more susceptible to variety of disruptive events, including natural disasters, man-made attacks, and common failures due to their complexity, globalization, and interconnected structures. Hence, it is important to design resilient supply chains which are capable of withstanding and recovering rapidly from disruptive events. This paper first explores the key drivers that contribute to the design of resilient supply chains based on the notion of absorptive, adaptive and restorative capacities. Second, it introduces a generic conceptual framework comprising five key phases: threat analysis, resilience capacity design, resilience cost evaluation, resilience quantification, and resilience improvement. The primary challenge to the literature of system resilience is how to measure it qualitatively. Findings from literature indicate that many of the drivers to the system resilience are qualitative such as staff cooperation and collaboration during disruptive events, level of preparation against natural disaster, among others. To fill the gap between qualitative and quantitative assessment of resilience, we employed Bayesian network to quantify the system resilience. Bayesian network is a rigorous tool for measuring risks under uncertainty, representing dependency between causes and effects, and making special types of reasoning. Additionally, it is capable of handling both qualitative and quantitative variables in terms of probability. We implemented Bayesian network for quantifying the supply chain system resilience of sulfuric acid manufacturer in Iran. Different scenarios have been defined and implemented to identify critical variables that are susceptible to the system resilience of sulfuric acid manufacturer.     

基于Agent的可重构装配线制造执行系统

针对制造执行系统存在的问题,根据可重构制造模式的理念,设计基于CORBA和多Agent的可重构装配线制造执行系统的体系结构,实现制造执行系统的可重构性和可集成性,构建系统的IDEF0功能模型,给出Agent结构模型及装配资源聚类方法。实际应用表明该系统具有良好的实用性,能满足企业需求。     

Characterization of reconfigurable Stewart platform for contour generation

The limited treatment available for Stewart platform characteristics leads to the lack of an efficient methodology for determining the optimum geometry for different tasks. In this paper, an effort is made to characterize the parameters for developing a reconfigurable Stewart platform for the contour generation application. A solution is provided through the formulation of dimensionless parameters in combination with a study on the generic parameters like configuration. The variable geometry approach for the reconfiguration of Stewart platform has been adopted for four different platforms, and a generic approach is formulated after studying different parameters. A stiffness model developed for contour generation application is used in tandem with this generic approach to identify the trajectory with maximum stiffness for complex contours. The proposed methodology provides a holistic approach to develop a complete set of design tool to choose the optimum geometry for any new reconfigurable Stewart platform to be developed.     

基于节点修复的网络化指挥信息系统弹性分析模型

提出一种基于节点修复的网络化指挥信息系统弹性分析模型。首先,确立了网络化指挥信息系统弹性的概念,构建了指挥信息系统网络模型,对网络级联失效和恢复过程进行了描述;然后,在建立负载分配模型和节点修复模型的基础上,根据网络化指挥信息系统弹性过程构建了弹性度量模型;最后,进行仿真分析,计算不同模型参数下的网络弹性。结果表明,恢复概率和平均修复时间等参数对网络弹性的影响显著,为提高网络化指挥信息系统的弹性提供了参考。     

Design and analysis of a reconfigurable discrete pin tooling system for molding of three-dimensional free-form objects

This paper presents the design and analysis of a new reconfigurable tooling for the fabrication of three-dimensional (3D) free-form objects. The proposed reconfigurable tooling system comprises a set of matrices of a closely stacked discrete elements (i.e., pins) arranged to form a cavity in which a free-form object can be molded. By reconfiguring the pins, a single tool can be used in the place of multiple tools to produce different parts with the involvement of much lesser time and cost. The structural behavior of a reconfigurable mold tool under process conditions of thermoplastic molding is studied using a finite element method (FEM) based methodology. Various factors that would affect the tool behavior are identified and their effects are analyzed to optimally design a reconfigurable mold tool for a given set of process conditions. A prototype, open reconfigurable mold tool is developed to present the feasibility of the proposed tooling system. Several case studies and sample parts are also presented in this paper.     

MES-integrated digital twin frameworks

Industry 4.0-based manufacturing systems are equipped with Cyber-Physical Systems that are characterized by a strong interlinkage between the real world and the digital one: actions in one world have an impact on the other. In this paradigm, Digital Twins (DT) are defined as simulation models that are both getting data from the field and triggering actions on the physical equipment. However, most of the claimed DT in literature are only replicating the real system in a synchronized fashion, without feeding back actions on the control system of the equipment. In literature, these are referred to as Digital Shadows (DS). The paper proposes a way to integrate a DS simulation model with the Manufacturing Execution System (MES) in this way creating a DT. The MES-integrated DT is used for decision making thanks to the presence of an intelligence layer that hosts the rules and the knowledge to choose among alternatives. The paper proposes two frameworks based on the MES-integrated DT: one for managing error states and one for triggering disassembly processes as a consequence of low assembly quality. The DT simulation is developed and integrated with the MES of the Industry 4.0 Laboratory at the School of Management of Politecnico di Milano, where the proposed frameworks have been tested and validated.     

Intelligent workload balance control of the assembly process considering condition-based maintenance

Balancing the workloads of workstations is key to the efficiency of an assembly line. However, the initial balance can be broken by the changing processing abilities of machines because of machine degradation, and at some point, re-balancing of the line is inevitable. Nevertheless, the impacts of unexpected events on assembly line re-balancing are always ignored. With the advanced sensor technologies and Internet of Things, the machine degradation process can be monitored continuously, and condition-based maintenance can be implemented to improve the health state of each machine. With the technology of robotic process automation, workflows of the assembly process can be smoothed and workstations can work autonomously together. A higher level of process automation can be achieved. Real-time information of the processing abilities of machines will bring new opportunities for automated workload balance via adaptive decision-making. In this study, a fuzzy control system is developed to make real-time decisions to balance the workloads based on the processing abilities of workstations, given the policy of condition-based maintenance. Fuzzy controllers are used to decide whether to re-balance the assembly line and how to adjust the production rate of each workstation. The numerical experiments show that the buffer level of the assembly line with the proposed fuzzy control system is lower than that of the assembly line without any control system and the buffer level of the assembly line with another control system is the lowest. The demand can always be satisfied by assembly lines except the one with another control system since there is too much production loss sacrificed for the low buffer level. The sensitivity analysis of the control performance to the parameter settings is also conducted. Thus, the effectiveness of the proposed fuzzy control system is demonstrated, and intelligent automation can improve the performance of the assembly process by the fuzzy control system since real-time information of the assembly line can be used for adaptive decision-making.     

Analysis of a linear walking worker line using a combination of computer simulation and mathematical modeling approaches

It has become increasingly important in the last few years to develop rapid, dynamic, responsive and reconfigurable manufacturing processes and systems. This is because manufacturing enterprises are now being forced to develop and constantly improve their production systems so that they can quickly and economically react to unpredictable conditions such as varying production volumes and product variants with small lot size, high quality and low costs. One effective method to achieve this is to create a more flexible, highly skilled and agile workforce capable to perform multiple or all the required tasks in a production area where the system can be reconfigured easily as needed to accommodate changes of production requirement on a daily or weekly basis.This paper presents a study of a so-called linear walking worker assembly line based on a combination of computer simulation and mathematical analysis. The linear walking worker assembly line is a flexible assembly system where each worker travels down the line carrying out each assembly task at each station; and each worker accomplishes the assembly of a unit from start to finish. This design attempts to combine the flexibility of the U-shaped moving worker assembly cell with the efficiency of the conventional fixed worker assembly line. The paper aims to evaluate one critical factor of in-progress waiting time that affects the overall system performance providing a dynamic simulation outlook as well as an insight into the mechanism of such a flexible and reconfigurable manufacturing system.     

Reconfigurable and transportable container-integrated production system

In this paper, the concept and the prototype realization of a novel reconfigurable small-footprint manufacturing system in a transportable container is presented. The containerized format enables transportation of the system to provide on-site manufacturing, enabling the benefits of localized service delivery without duplication of equipment at multiple locations.Three industrial product use cases with varying manufacturing and performance requirements were analysed. All of the use cases demanded highly customized products with high quality in low production volumes. Based on their requirements, a general system specification was derived and used to develop a concept for the container-integrated factory.A reconfigurable, modular manufacturing system is integral to the overall container concept. Production equipment was integrated in the form of interchangeable process modules, which can be quickly connected by standard utility supply and control interfaces. A modular and self-configuring control system provides assisted production workflow programming, while a modular process chain combining Additive Manufacturing, CNC milling, precision assembly and cleaning processes has been developed.A prototype of the container-integrated factory with reconfigurable process modules and control system has been established, with full functionality and feasibility of the system demonstrated.     

Using adjustable autonomy and human-machine cooperation to make a human-machine system resilient - Application to a ground robotic system

This study concerns autonomous ground vehicles performing missions of observation or surveillance. These missions are accomplished under the supervision of human operators, who can also remotely control the unmanned vehicle. This kind of human-machine system is likely to face perturbations in a dynamic natural environment. However, human operators are not able to manage perturbations due to overload. The objective of this study is to provide such systems with ways to anticipate, react and recover from perturbations. In other words, these works aim at improving system resilience so that it can better manage perturbations. This paper presents a model of human-robot cooperative control that helps to improve the resilience of the human-machine system by making the level of autonomy adjustable. A formalism of agent autonomy is proposed according to the semantic aspects of autonomy and the agent’s activity levels. This formalism is then used to describe the activity levels of the global human-machine system. Hierarchical decision-making methods and planning algorithms are also proposed to implement these levels of activity. Finally, an experimental illustration on a micro-world is presented in order to evaluate the feasibility and application of the proposed model.