Linear constraint programming for cost-optimized configuration of modular assembly systems

In this paper, we develop an optimization model for providing a logical layout for reconfigurable assembly systems from a library of available equipment modules. The design problem addresses the challenges in equipment selection to build workstations and subsequently the entire assembly system. All the available equipment modules are assumed to be modular and each of them retains a subset of skills (capabilities). The set of all available equipment modules, their skills, mode of physical connectivity (ports) and costs are known. The objective is to minimize the overall equipment cost without violating their physical connectivity (ports) constraints and the precedence constraints of the assembly process requirements. The analysis of the problem and the state-of-art review steered us to the following: (1) the design problem is very closely related to the assembly line balancing problems; (2) a few Genetic Algorithm (GA) based approaches are already available for the capital cost optimization of multi-part flow-line (MPFL) configurations that includes the operational precedence constraints; (3) to our knowledge, this is the first work to combine the equipment physical connectivity constraints with task precedence in order to provide a valid and optimal configuration solution. A formalized mathematical model is developed to select suitable subsets of equipment modules and group them into workstations to construct an optimal logical layout. A number of scenarios based on an industrial case study are simulated and the results are analysed to evaluate the performance of the proposed models

Design Requirements for Effective Hybrid Decision Making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

Design requirements for effective hybrid decision making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

Skill-based reconfiguration of industrial mobile robots

Caused by a rising mass customisation and the high variety of equipment versions, the exibility of manufacturing systems in car productions has to be increased. In addition to a exible handling of production load changes or hardware breakdowns that are established research areas in literature, this thesis presents a skill-based recon guration mechanism for industrial mobile robots to enhance functional recon gurability. The proposed holonic multi-agent system is able to react to functional process changes while missing functionalities are created by self-organisation. Applied to a mobile commissioning system that is provided by AUDI AG, the suggested mechanism is validated in a real-world environment including the on-line veri cation of the recon gured robot functionality in a Validity Check. The present thesis includes an original contribution in three aspects: First, a recon - guration mechanism is presented that reacts in a self-organised way to functional process changes. The application layer of a hardware system converts a semantic description into functional requirements for a new robot skill. The result of this mechanism is the on-line integration of a new functionality into the running process. Second, the proposed system allows maintaining the productivity of the running process and exibly changing the robot hardware through provision of a hardware-abstraction layer. An encapsulated Recon guration Holon dynamically includes the actual con guration each time a recon guration is started. This allows reacting to changed environment settings. As the resulting agent that contains the new functionality, is identical in shape and behaviour to the existing skills, its integration into the running process is conducted without a considerable loss of productivity. Third, the suggested mechanism is composed of a novel agent design that allows implementing self-organisation during the encapsulated recon guration and dependability for standard process executions. The selective assignment of behaviour-based and cognitive agents is the basis for the exibility and e ectiveness of the proposed recon guration mechanism

Diagnosis of an EPS module

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e ComputadoresThis thesis addresses and contextualizes the problem of diagnostic of an Evolvable Production System (EPS). An EPS is a complex and lively entity composed of intelligent modules that interact through bio-inspired mechanisms, to ensure high system availability and seamless reconfiguration. The actual economic situation together with the increasing demand of high quality and low priced customized products imposed a shift in the production policies of enterprises. Shop floors have to become more agile and flexible to accommodate the new production paradigms. Rather than selling products enterprises are establishing a trend of offering services to explore business opportunities. The new production paradigms, potentiated by the advances in Information Technologies (IT), especially in web related standards and technologies as well as the progressive acceptance of the multi-agent systems (MAS) concept and related technologies, envision collections of modules whose individual and collective function adapts and evolves ensuring the fitness and adequacy of the shop floor in tackling profitable but volatile business opportunities. Despite the richness of the interactions and the effort set in modelling them, their potential to favour fault propagation and interference, in these complex environments, has been ignored from a diagnostic point of view. With the increase of distributed and autonomous components that interact in the execution of processes current diagnostic approaches will soon be insufficient. While current system dynamics are complex and to a certain extent unpredictable the adoption of the next generation of approaches and technologies comes at the cost of a yet increased complexity.Whereas most of the research in such distributed industrial systems is focused in the study and establishment of control structures, the problem of diagnosis has been left relatively unattended. There are however significant open challenges in the diagnosis of such modular systems including: understanding fault propagation and ensuring scalability and co-evolution. This work provides an implementation of a state-of-the-art agent-based interaction-oriented architecture compliant with the EPS paradigm that supports the introduction of a new developed diagnostic algorithm that has the ability to cope with the modern manufacturing paradigm challenges and to provide diagnostic analysis that explores the network dimension of multi-agent systems

An AutomationML model for plug-and-produce assembly systems

This paper aims to support the creation of high performance ‘Plug-and-Produce’ systems by proposing a new semantic model that targets the use of AutomationML (AML). In this direction, the focus is narrowed to the self-description of equipment modules that highlights the use of ‘Skill’ concept. An insight description on how the concept of ‘Skill Recipe’ can be used to execute the equipment ‘Skills’ to fulfil the product's assembly requirements is also provided. This is viewed as a critical concept to achieve high performance in ‘Plug-and-Produce’. To translate the base semantic definitions, we have developed new libraries that are fully compliant with the AML standard. The main purpose of using AML in this context is to bridge production and other engineering domains. An overview of the literature that covers the past and current trends in data exchange and standards is presented, while pointing out the existing challenges and limitations. The vision of this paper is to support the standardization effort of integrating information for design, build, ramp-up and operation of production systems. Hence, this approach elucidates the use of existing AML concepts to model and instantiate Product, Process and Resource (PPR), and the underlying definitions such as: ‘Skills’, ‘Skill Recipes’ and ‘Skill Requirements’. Finally, this paper illustrates the implementation of this approach in AML with a help of an industrial case study demonstrated within the openMOS project

Lightweight robust behavior industrial agent methodology

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresAssembly systems today face significant pressure to provide highly adaptable and quickly deployable solutions in order to deal with unpredictable changes according to market trends. However, control of assembly processes are dominated by the use of Programmable Logical Controllers (PLC) which do not provide the necessary mechanisms to easily deal with these challenges. The concept of agent-based control has been introduced as a solution to deal these challenges and support new production paradigms based on the plug and produce concept. However, this solution has not yet been proven to be a real alternative to the traditional PLC approach in terms of performance. This work is investigating the use an approach that is able to benefit from the relative advantages of both PLC and agents solutions. A new hybrid architecture is presented which combines the functionalities of a PLC with those of industrial agents. The focus is on assessing the performance of this approach and help change the minds of an industry averse to changes

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime

Design requirements for effective hybrid decision making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation

Improve the Performance of Industrial Agents using Fog Computing

In the last decade, the market requirements have been increasing by demanding numerous different products being highly customizable. Given this need, the necessity for dynamic and flexible production lines are a high priority to meet this change. A traditional approach is not enough to meet the market demand and due to this, several paradigms have been coined out to try and solve this problem. The proposed approach is related to communication between the shop-floor modules in order to create different products. This work proposes an architecture where an integration layer will join a Multiagent System capable of the more recent production paradigms with legacy hardware that is present in the more traditional factories in order to have different products being produced in the same production line. This architecture that revolves an interface that can be used by the agents in the factory in order to use the hardware modules to create a different product if need be. The main features of this project is the fact that by using datamodels and an interface created, it can be easily plugged new stations with different tools to modify the product thus increasing the amount of products that can be created