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This paper aims to provide a method and decision support tool to enhance swift reconfiguration of Plug&Produce (P&P) systems in the presence of continuously changing production orders.

The paper reviews different production scenarios and system design and configuration methods and more particularly specifies the need of decision support tools for P&P systems that integrate configuration and planning activities. This problem is then addressed by proposing a method that helps reduce the solution space of the reconfiguration problem and allows the timely selection of the most promising reconfiguration alternative.

The proposed method was found to be helpful in reducing the reconfiguration alternatives that need to be considered and in selecting the most promising one for different orders. The advantages and limitations of this method are identified, and an illustrative test case of the approach is presented, corroborating the method applicability in the absence of large queues in the system.

This paper addresses a less explored domain within the P&P systems research field, which is the system reconfiguration. It proposed a method to support system validation and reconfiguration jointly with an illustrative test case. This represents an original contribution to the P&P research field, and it can have impact in improving agility and decreasing the complexity of reconfiguration activities to cope with constantly changing production orders.

Current major roadmapping efforts have all clearly underlined that true industrial sustainability will require far higher levels of systems' autonomy and adaptability. In accordance with these recommendations, the Evolvable Assembly Systems (EAS) has aimed at developing such technological solutions and support mechanisms. Since its inception in 2002 as a next generation of production systems, the concept is being further developed and tested to emerge as a production system paradigm. The essence of evolvability resides not only in the ability of system components to adapt to the changing conditions of operation, but also to assist in the evolution of these components in time. Characteristically, Evolvable systems have distributed control, and are composed of intelligent modules with embedded control. To assist the development and life cycle, a methodological framework is being developed. After validating the process‐oriented approach (EC FP6 EUPASS project), EAS now tackles its current major challenge (FP7 IDEAS project) in proving that factory responsiveness can be improved using lighter multi‐agent technology running on EAS modules (modules with embedded control). The purpose of this paper is to detail the particular developments within the IDEAS project, which include the first self re‐configuring system demonstration and a new mechatronic architecture.

The paper covers the development of a plug & produce system for FESTO AG. The work covers the background methodology and details its constituents: control system, architecture, design methodology, and modularity. Specific detail is reserved for the configuration approach which integrates several tools, and the commercially available control boards. The latter have been specifically developed for distributed control applications.

The paper details probably the first self‐configuring assembly system at shop‐floor level. This is one of the very first industrial plug & produce systems, in which equipment may be added/removed with no programming effort at all.

The paper reports the findings and development carried out within the framework of a single project. It also clarifies that the solution is not a general panacea for all the issues within assembly.

The implications are quite large as the work proves the validity of an approach that could change our way of designing and building assembly systems. In the words of an industrial partner, this is “a new way of engineering assembly systems”.

Should this approach be used in industry then the implications could be huge. It would, for example, mean that new services are created, whereby assembly system modules are leased to users through a network of depots, rather than bought at a high cost. The system modules also have a far longer lifespan, implying very good ecological solutions.

The highly original paper describes what is probably one of the very first projects to show that distributed control at shop‐floor level is viable and technologically feasible.

The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.

The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.

By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.

The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.

The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

This paper aims to describe a new methodology for controlling highly flexible automated manufacturing cells for use in aerospace manufacturing and repair.

The design methodology and rational of the FLEXA control architecture are described along with it implementation and testing.

The trials completed so far show that the level of flexibility required can be achieved both at factory, or enterprise level, and at shop floor level.

This work has significant practical implications through its direct applicability for aerospace and other automated manufacturing processes.

The originality of the paper lies in the truly flexible nature of the control system described and its ability to mimic traditional cell control architectures but be expanded through the use of virtual Programmable Logic Controller to control any number of cells without the need for significant extra hardware.

Increasingly, dynamic market environments lead to growing complexity in manufacturing and pose a severe threat for the competitiveness of manufacturing companies. Systematic guidance to manage this complexity, especially in the context of Industry 4.0 and the therewith rising trends such as digitalization and data-driven production optimization, is lacking. To address this deficit a case-based reasoning (CBR) system for providing knowledge about managing complexity in Industry 4.0 is presented.

First, the explicit knowledge representation for managing complexity in IT-based manufacturing is introduced. Second, the CBR process step to retrieve knowledge from an artificially composed case base with in total 70 cases of data-based complexity management in the context of Industry 4.0 is set out. Third, knowledge transfer alongside several maturity levels of information technology capabilities of manufacturing systems for reuse in new problem scenarios is introduced.

The paper comprises the conceptual approach for designing a CBR system to support data-based complexity management in manufacturing systems. Furthermore, the appropriateness of the CBR system to provide applicable knowledge for reducing and managing complexity in corporate practice is shown.

The presented research results are evaluated in the course of an embedded single case study and may therefore lack generalizability. Future research to test and enhance the appropriateness of the developed CBR system will strengthen the research contribution.

The paper provides a novel approach to systematically support knowledge transfer for data-based complexity management by transferring the well-known and established methodology of CBR to the rising application domain of manufacturing systems in the context of Industry 4.0.

In this study, we introduce and discuss a concept of fuzzy plug‐ins and investigate their role in system modeling. Fuzzy plug‐ins are rule‐based constructs augmenting a given global model (arising in the form of some regression relationship, neural network, etc.) in the sense that they compensate for the mapping errors produced by the global model. The proposed design method develops around information granules of error defined in the output space and the induced fuzzy relations expressed in the space of input variables. The construction of the linguistic granules is carried out with the aid of context‐based fuzzy clustering – a generalized version of the well‐known FCM algorithm that is well‐suited to the design of fuzzy sets and relations being used as a blueprint of the plug‐ins. An overall modeling architecture combining the global model with its plug‐ins is discussed in detail and a complete design procedure is provided. Finally, some illustrative numerical examples are shown as well.

This paper aims to determine the optimum arrangement of a reverse osmosis system in two methods of plug and concentrate recycling.

To compare the optimum conditions of these two methods, a seawater reverse osmosis system was considered to produce fresh water at a rate of 4,000 m3/d for Mahyarkala city, located in north of Iran, for a period of 20 years. Using genetic algorithms and two-objective optimization method, the reverse osmosis system was designed.

The results showed that exergy efficiency in optimum condition for concentrate recycling and plug methods was 82.6 and 92.4 per cent, respectively. The optimizations results showed that concentrate recycling method, despite a 36 per cent reduction in the initial cost and a 2 per cent increase in maintenance expenses, provides 6 per cent higher recovery and 19.7 per cent less permeate concentration than two-stage plug method.

Optimization parameters include feed water pressure, the rate of water return from the brine for concentrate recycling system, type of SW membrane, feedwater flow rate and numbers of elements in each pressure vessel (PV). These parameters were also compared to each other in terms of recovery (R) and freshwater unit production cost. In addition, the exergy of all elements was analyzed by selecting the optimal mode of each system.

THE ability to detect an impending failure in an aircraft engine mechanical power system, at an early stage, where expensive and possibly catastrophic system failures can be prevented, will provide enhanced aircraft safety by minimising the possibility of a serious engine failure, and the need for the pilot to shut down an engine during flight with all the attendant emergency ramifications that can arise. This will also improve the utilisation of the aircraft, by the scope to plan unscheduled engine removals to suit the aircraft downtime, and it will reduce the turnround time and costs to effect the necessary repairs; particularly if the skill of detection can also pinpoint the area of distress with accuracy.

This paper aims to develop an easily reconfigurable assembly cell.

Some functions are implemented to resolve problems associated with physical reconfiguration of an agent‐based robotic assembly cell, such as position calibration and workspace allocation.

The implemented prototype assembly cell is composed of industrial manipulators and a belt conveyor. Installation of a new manipulator and assembly execution are successfully demonstrated on the prototype cell.

In the developed assembly system, installation and removal of assembly devices are easily performed so that it can adapt to changes in the manufacturing environment quickly.

The developed system does not use specially designed hardware. Easy reconfiguration is enabled using conventional devices such as manipulators and belt conveyors.