NL EN. Summary: The book offers an integrated vision on Cloud and HPC, Big Data, Analytics and virtualization in computing-oriented manufacturing, combining information and communication technologies, service-oriented control of holonic architectures as well as enterprise integration solutions based on SOA principles. Dewey: Artificial intelligence. Industrial engineering. Computational Intelligence.
APA: Borangiu, T. Chicago: Borangiu, Theodor. Erlang is a functional programming language with strong scalability, concurrency and fault-tolerance characteristics, which prove to be beneficial when applied to the manufacturing control context. The case study used in this paper is the holonic control of a modular conveyor system; this implementation was chosen to demonstrate the advantages that Erlang can offer as implementation language for holonic systems. This paper treats a topical issue for present manufacturing systems, which is the needed adaptability when manufacturing orders are received in an unpredictable way.
To face such cases, a rescheduling mechanism is necessary and such a possibility is investigated for a holonic system that materializes its coordination through a combination between the Contract Net Protocol and Distributed Constraint Satisfaction Problem. The proposed method is investigated for a case study, by doing simulation experiments with the system coloured Petri net model.
The results are analysed for the cases when the new command received during execution is more or less important than the ongoing ones. An increasing demand to provide customised products creates challenges for manufacturing organisations. This poses a need to understand the characteristics required for manufacturing systems to handle customisation. In this study, 3D printing technology is assessed as an enabler for customisation. Additionally, the requirements of manufacturing systems with respect to configuration and control co-ordination are explored.
A demonstrator is implemented to integrate 3D printing with conventional manufacturing, using an agent based distributed control system that co-ordinates the customisation of products and the order management. Hybrid manufacturing control architectures merge the benefits of hierarchical and heterarchical approaches.
Disturbances can be handled at upper or lower decision levels, depending on the type of disturbance, its impact and the time the control system has to react. This paper focuses particularly on a disturbance handling mechanism at upper decision levels using a rescheduling manufacturing method. Such rescheduling is more complex that the offline scheduling since the control system must take into account the current system status, obtain a satisfactory performance under the new conditions, and also come up with a new schedule in a restricted amount of time.
Then, this paper proposes a simple and generic rescheduling method which, based on the satisfying principle, analyses the trade-off between the rescheduling time and the performance achieved after a perturbation. The proposed approach is validated on a simulation model of a realistic assembly cell and results demonstrate that adaptation of the rescheduling time might be beneficial in terms of overall performance and reactivity.
Thriving and challenging market trends led to changes in the manufacturing industry. Production lines that need to adapt to customisable products on the fly emerged. By applying communication and sensors to the shop-floor, along with Industry 4. The growing amount of sensors led to an exponential boom of the amount of data available, creating the concept of Smart Factory. There are technologies capable of doing this, even though only some are capable of guaranteeing Smart Factory requirements, such as real-time.
This paper presents an application of the measurements-based AHP to define a two-stage algorithm for product-driven systems control, in case of an unexpected event.
The methodology is detailed on a simple case study. Production planning and control and more generally taking a decision in the context of production systems often consider that input information are known, static and predictable. However, uncertainties on data and perturbations are recorded in the genetic of every production system. For instance, it is impossible to know exactly the level of the demand for a product, the availability of resources, etc.
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Dealing with this issue raises the question of the ability to take robust decisions against uncertainty off-line or the ability to be flexible on-line. This paper proposes to analyse how Product Driven Systems—as reactive systems against unpredicted perturbations—can be part of operational research solution process against perturbations.
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Moreover, an overview of models and approaches for dealing with uncertainty in Operational Research is given and a first proposition is made to apply these elements into PDS as decision-making-against-perturbations engines. The paper presents design and implementing considerations for an agent-based environment monitoring and control system dedicated to a radiopharmaceuticals production line.
The paper describes the environment parameters and defines the HVAC process models. The facility environment control system is developed in holonic approach, with three basic holons and one expertize holon. An implementing solution and integration of the environment control system with the radiopharmaceutical production management system is described. Experimental results and conclusions are finally presented. This paper analyses the new requirements for real time resource management systems based on multi-agent technology.
It shows the growing demand for developing autonomous systems which combine resource allocation, scheduling, optimization, communication with users and control in one cycle and can respond rapidly to unexpected events in real time. To solve the problem, cyber-physical multi-agent systems are considered. The paper also analyses the new impact which such systems bring into design of modern systems on the way from smart Internet of Things—to new organizations and ways of user motivation.
Avoiding myopia, suboptimal behaviour, caused by the limited information horizon and computation capacity of agents, has been recognized as a major design challenge for the future academic development and industrial adoption of distributed production control systems.
In  existing literature from various research streams has been reviewed to classify design decisions that can be made to avoid myopic decision making. In the present paper, this model will be validated by mapping different paradigms of distributed control onto it.
Through this exercise, an initial validation of the proposed classification model can be attained and a starting point for a classification of existing distributed production control approaches based on design features is provided. This will help designers of distributed architectures in production control to better understand their design space, take deliberate steps towards the avoidance of myopic behaviour, and identify unexplored areas within the design space.
Most modern manufacturing systems rely on constantly seeking new solutions to better fulfil their manufacturing objectives. In spite of the current research efforts, real reconfiguration solutions are still lacking automated tools that support dynamic and runtime reconfigurations by discovering new adaptation needs and opportunities and, thus, explore possible actions leading to new system configurations.
Most of the service changes triggers rely on reactive events, where decisions come from a centralized decision-maker and are performed manually. Based on these facts a service-oriented multi-agent systems architecture is described aiming at actively promoting service reconfiguration e. This paper describes the processes that decide which service reconfiguration should be applied to each circumstance.
The developed prototype for a flexible manufacturing system case study allowed verifying the feasibility of the proposed dynamic service reconfiguration solution in different scenarios. In the literature, different approaches are proposed to deal with both these problems. Our aim in this paper is to present a literature review of such researches.
Nowadays smart cities are becoming more and more a hot topic in the technological world. Some different approaches emerged and many city departments approved investigation and implementation of the smart city technology in their cities.
The implementation of these processes is becoming a landmark for the modern cities. This paper proposes a generic semantic model to easily plug and manage heterogeneous smart devices and areas of cities, in order to integrate all the diverse components that constitute a fully integrated and functional smart city environment. This semantic model can be used in the most diverse city scenarios; to demonstrate it, a specific scenario is presented in this paper, describing the usage of the proposed semantic model to detect new components and share information among the smart components.
The small firms can be satisfied with their quick reaction to customer requests and their creativity but they meet big issues internally about the products sold. These issues put ahead a lack of information when the product is out of the SME. After an analysis of the origin of the problem, the paper proposes to use the active product concept as a key element to solve the problem. New production systems are highly reconfigurable and interact with dynamic industrial environments. Their modelling, simulation and analysis of the operations and evaluation of performances are now much more complex than in the past when system had a static and predefined behaviour.
This paper proposes a method to describe and analyse complex production systems, based on utilization of FSA Finite State Automaton. This approach is enabling better understanding and sharing with stakeholders of how a system works, but it is also a good basis for computer based simulation and control. The interaction with external environments is structured in terms of External Events inputs and Trigger Outputs.
The analysis of the system state evolution in the time domain provides the possibility to calculate KPIs Key Performance Indicators in specific conditions or their evolution. In this paper a simplified language syntax describing the automaton including output generation and triggering of external functions of the production environment is proposed.
The approach is implemented and demonstrated in a particular industrial domain: industrial machinery fabrication sector. This paper, after describing the main pillars of the PERFoRM system architecture, focuses on mapping the system architecture into four industrial use cases aiming to validate the system architecture design before its deployment in the real environments. In modern manufacturing, high volumes of data are constantly being generated by the manufacturing processes. However, only a small percentage is actually used in a meaningful way.
Petri Nets allow modelling RMSs in an abstract way and to make specification, refinement, verification and validation of these systems. Moreover, the use of Stochastic Petri Nets allows the designer to catch more indispensable aspects time and stochastic events of RMSs, thus the designer can make performance evaluation. In order to study explicitly the reconfigurability, in Petri nets, several works proposed the extension of PN called reconfigurable Petri nets.
However, these extensions do not deal yet with stochastic Petri nets.