Agent-based strategic planner for the production of samll lots of complex products: theoretical and practical perspectives

This paper presents a strategic planner that assists the decision-makers to take strategic decisions on short term to respond faster and efficiently to unexpected events in the ramp-up production of complex and highly customized products, namely in situations of peak of demand, late change requests and immature technology. This tool combines the flexibility of multi-agent systems with the optimization capability of mathematical optimization solvers. The application of the strategic planner is illustrated by playing iterative what-if games supporting implementation of mitigation strategies addressing a real use case of a peak demand of a specific product.The research leading to these results has received funding from the European Union Seventh Frame-work Programme FP7 ARUM project, under grant agreement n° 314056info:eu-repo/semantics/publishedVersio

What-if game simulation in agent-based strategic production planners

In the nowadays highly unstable manufacturing market, companies are faced, on a daily basis, with important strategic decisions, such as “does the company has the necessary capacity to accept a high volume order?” or “what measures need to be implemented if the product demand increases x% a year?”. Decision-makers, i.e. company’s managers, rely on their experience and insights supported by classical tools to take such decisions. Classical mathematical solvers or agent-based systems are typical architectural solutions to implement strategic planning tools to support decision-makers on this important task. Within the ARUM (Adaptive Production Management) project, a hybrid strategic planning tool was specified and developed, combining the optimization features of classical solvers with the flexibility and agility of agent systems. This paper briefly presents such architecture and focuses on the generation of the “what-if game” mechanism to support the generation of more intelligent and dynamic planning solutions.The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007- 2013 under grant agreement n° 314056.info:eu-repo/semantics/publishedVersio

Industrial agents in the era of service-oriented architectures and cloudbased industrial infrastructures

The umbrella paradigm underpinning novel collaborative industrial systems is to consider the set of intelligent system units as a conglomerate of distributed, autonomous, intelligent, proactive, fault-tolerant, and reusable units, which operate as a set of cooperating entities (Colombo and Karnouskos, 2009). These entities are forming an evolvable infrastructure, entering and/or going out (plug-in/plugout) in an asynchronous manner. Moreover, these entities, having each of them their own functionalities, data, and associated information are now connected and able to interact. They are capable of working in a proactive manner, initiating collaborative actions and dynamically interacting with each other in order to achieve both local and global objectives.info:eu-repo/semantics/publishedVersio

Insider Threats in Emerging Mobility-as-a-Service Scenarios

Mobility as a Service (MaaS) applies the everything-as- \ a-service paradigm of Cloud Computing to transportation: a MaaS \ provider offers to its users the dynamic composition of solutions of \ different travel agencies into a single, consistent interface. \ Traditionally, transits and data on mobility belong to a scattered \ plethora of operators. Thus, we argue that the economic model of \ MaaS is that of federations of providers, each trading its resources to \ coordinate multi-modal solutions for mobility. Such flexibility comes \ with many security and privacy concerns, of which insider threat is \ one of the most prominent. In this paper, we follow a tiered structure \ — from individual operators to markets of federated MaaS providers \ — to classify the potential threats of each tier and propose the \ appropriate countermeasures, in an effort to mitigate the problems

Developing a method to search for the causes of uncertainty in a nascent transport planning project

PhD ThesisThe transport planning decision process is, in theory, underpinned by rational analysis of travel behaviour and application of transport economics but project outcomes do not always follow the results of that analysis. Uncertainty is evident at all stages of the project development; as the concept emerges and as it moves through the subsequent assessment and decision processes. This research has investigated and demonstrated a method that identifies uncertainty focussing on the early stages of the project lifecycle and also provides an understanding of the factors that drive it. The method used a backcast scenario to elicit the causal relationships between elements of the planning and decision process in structured interviews with stakeholders. Qualitative analysis techniques were used to identify the active elements of the process, the causality between the elements was explored using the Cross Impact Matrix Model to evaluate their influences and dependencies and identify those driving uncertainty in the planning process. In this research, the Cross Impact Matrix Model was extended to analyse stakeholder opinions both individually and collectively, and investigation was undertaken into the parameter sensitivity of the analysis method. The case study was based on a disused railway where several studies into re-opening it have resulted in contradictory views on its mode of use and on the achievable benefits. In the scenario used in the case study, the rail service is re-instated for light rail use in conjunction with a new sustainable urban area anchored on an existing small village. The findings in this case study were that presence of strong leadership and collaboration between Local Authorities were the most influential determinants for progress and the prime causes of uncertainty were the economic environment, planning policies, and perceptions of passenger utility. Although these results emerged from a specific scenario, the methodology was demonstrated to be a powerful generic tool to identify the elements that create criticalities in planning for any scheme

Investigating individual preferences for new mobility services: the case of “mobility as a service” products

In just a few years, the Mobility as a Service (MaaS) concept has gone from an idea discussed by very few, to being a prominent topic in any transportation related debate. However, within this time, there have only been few rigorous studies that explore the various aspects of MaaS. This thesis aims to contribute to existing knowledge by providing empirical evidence on individual preferences for MaaS plans and their components. In doing so, first desk-research is conducted to summarise existing MaaS schemes and outline the MaaS ecosystem. Next, MaaS surveys that are able to capture individual preferences for MaaS products are designed and specific challenges in the design process identified. The MaaS surveys, including MaaS plan stated preference experiments, are applied in two case study areas of London and Greater Manchester. Using the novel data collected, individual preferences for MaaS plans are examined using two distinct studies: (1) a mixed methods research conducted in London, which expands the survey by adding a qualitative (in-depth interview) element to examine user preferences for MaaS plans and the ways individuals choose between them; and (2) a latent class choice model based on data collected from Manchester to examine whether there is heterogeneity in preferences. Finally, implications for industry and policy stakeholders are discussed as well as interventions that can best support the widespread adoption of MaaS. The results of this thesis show there is interest in the concept of MaaS among potential users as many see value in a single app that integrates different transport modes into a single service. In general, individuals are hesitant in purchasing pre-payed MaaS plans and would be more comfortable with a pay-as-you-go product option. While many people are reluctant towards MaaS plans, the results indicate that heterogeneity exists in preferences towards them and there are different user groups based on socio-demographic characteristics and current mobility habits. Smaller, less expensive plans including modes such as public transport and bike sharing can be used to target students or middle-income people with have high overall mode usage. Larger, more expensive plans that include modes such as taxi and car sharing in addition to public transport, will be attritive to individuals who are likely younger, male, well-educated, have higher income and already use many transport modes. Older population groups, individuals with low income and those that do not use any transport modes or are uni-modal are least likely to adopt MaaS plans. The thesis also provides insights into individuals’ preferences towards transport modes within MaaS plans. The analysis showed that respondents classify modes within MaaS plans into three categories: ‘essential’ modes that are pivotal to the individual and which they most likely already frequently use; ‘considered’ modes are those that they would be willing to include but may not yet use; and ‘excluded’ modes are those that they definitely do not want in their plans and would eliminate any plan that included these. Public transport consistently proved to be an essential mode, while taxi, car sharing and bike sharing could be ‘essential’, ‘considered’ or ‘excluded’ depending on the characteristics of the individual. The main contributions of this thesis are the novel data collected in two case study cities about individuals’ preferences for MaaS plans and the findings gained through the analysis providing insights into possible target audiences and product designs for MaaS plans

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening ontrol structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems

Future of Supply Chain – Application of Robotics – The Flip Side of It

Abstract— This research talks about how supply chain management (SCM) is being developed using robotics and process automation, the challenges faced in the transition process, and whether such transition is desirable. While overall efficiency of the SCM process can be improved through the replacement of conventional manual jobs, such as storing, inspecting, sorting, handling, categorizing products, and data entry, the adoption of this cutting-edge technology in areas such as purchase and supply management remains dubious, unpredictable and still relatively unexplored, leaving considerable scope for further research and experimentation.Keywords— RPA, robotic, process, automation, robotic process automation, supply chain, management, SCM

NEGOSEIO: framework for the sustainability of model-oriented enterprise interoperability

Dissertation to obtain the degree of Doctor of Philosophy in Electrical and Computer Engineering(Industrial Information Systems)This dissertation tackles the problematic of Enterprise Interoperability in the current globally connected world. The evolution of the Information and Communication Technologies has endorsed the establishment of fast, secure and robust data exchanges, promoting the development of networked solutions. This allowed the specialisation of enterprises (particularly SMEs) and favoured the development of complex and heterogeneous provider systems. Enterprises are abandoning their self-centrism and working together on the development of more complete solutions. Entire business solutions are built integrating several enterprises (e.g., in supply chains, enterprise nesting) towards a common objective. Additionally, technologies, platforms, trends, standards and regulations keep evolving and demanding enterprises compliance. This evolution needs to be continuous, and is naturally followed by a constant update of each networked enterprise’s interfaces, assets, methods and processes. This unstable environment of perpetual change is causing major concerns in both SMEs and customers as the current interoperability grounds are frail, easily leading to periods of downtime, where business is not possible. The pressure to restore interoperability rapidly often leads to patching and to the adoption of immature solutions, contributing to deteriorate even more the interoperable environment. This dissertation proposes the adoption of NEGOSEIO, a framework that tackles interoperability issues by developing strong model-based knowledge assets and promoting continuous improvement and adaptation for increasing the sustainability of interoperability on enterprise systems. It presents the research motivations and the developed framework’s main blocks, which include model-based knowledge management, collaboration service-oriented architectures implemented over a cloud-based solution, and focusing particularly on its negotiation core mechanism to handle inconsistencies and solutions for the detected interoperability problems. It concludes by validating the research and the proposed framework, presenting its application in a real business case of aerospace mission design on the European Space Agency (ESA).FP7 ENSEMBLE, UNITE, MSEE and IMAGINE project