Customising with 3D printing: The role of intelligent control

© 2018 Elsevier B.V. The emergence of direct digital manufacturing creates new opportunities for the production of highly customised goods especially when it is combined with conventional manufacturing methods. Nevertheless, this combination creates a need for systems that can effectively manage and control the resulting distributed manufacturing process. In this paper, we explore three different configurations that can enable direct digital manufacturing for customisation, ranging from fully integrated to inter-organisational set up. Additionally, control requirements of such systems are developed and the suitability of intelligent control is explored. By ‘intelligent control’ we mean production control that is capable of assessing and interacting with the production environment and adapting production accordingly. We argue that the so called intelligent product paradigm provides a suitable mechanism for the development of such intelligent control systems. In this approach, the intelligent product directly co-ordinates with design agent, 3D printing agents and other conventional manufacturing system agents to schedule, assign and execute tasks independently. Via a case example of a realistic production system, we propose and implement such an intelligent control system and we analyse its feasibility in supporting 3D printing enabled customisation

Integrating CLIPS applications into heterogeneous distributed systems

SOCIAL is an advanced, object-oriented development tool for integrating intelligent and conventional applications across heterogeneous hardware and software platforms. SOCIAL defines a family of 'wrapper' objects called agents, which incorporate predefined capabilities for distributed communication and control. Developers embed applications within agents and establish interactions between distributed agents via non-intrusive message-based interfaces. This paper describes a predefined SOCIAL agent that is specialized for integrating C Language Integrated Production System (CLIPS)-based applications. The agent's high-level Application Programming Interface supports bidirectional flow of data, knowledge, and commands to other agents, enabling CLIPS applications to initiate interactions autonomously, and respond to requests and results from heterogeneous remote systems. The design and operation of CLIPS agents are illustrated with two distributed applications that integrate CLIPS-based expert systems with other intelligent systems for isolating and mapping problems in the Space Shuttle Launch Processing System at the NASA Kennedy Space Center

A multi-agent approach for design consistency checking

The last decade has seen an explosion of interest to advanced product development methods, such as Computer Integrated Manufacture, Extended Enterprise and Concurrent Engineering. As a result of the globalization and future distribution of design and manufacturing facilities, the cooperation amongst partners is becoming more challenging due to the fact that the design process tends to be sequential and requires communication networks for planning design activities and/or a great deal of travel to/from designers' workplaces. In a virtual environment, teams of designers work together and use the Internet/Intranet for communication. The design is a multi-disciplinary task that involves several stages. These stages include input data analysis, conceptual design, basic structural design, detail design, production design, manufacturing processes analysis, and documentation. As a result, the virtual team, normally, is very changeable in term of designers' participation. Moreover, the environment itself changes over time. This leads to a potential increase in the number of design. A methodology of Intelligent Distributed Mismatch Control (IDMC) is proposed to alleviate some of the related difficulties. This thesis looks at the Intelligent Distributed Mismatch Control, in the context of the European Aerospace Industry, and suggests a methodology for a conceptual framework based on a multi-agent architecture. This multi-agent architecture is a kernel of an Intelligent Distributed Mismatch Control System (IDMCS) that aims at ensuring that the overall design is consistent and acceptable to all participating partners. A Methodology of Intelligent Distributed Mismatch Control is introduced and successfully implemented to detect design mismatches in complex design environments. A description of the research models and methods for intelligent mismatch control, a taxonomy of design mismatches, and an investigation into potential applications, such as aerospace design, are presented. The Multi-agent framework for mismatch control is developed and described. Based on the methodology used for the IDMC application, a formal framework for a multi-agent system is developed. The Methods and Principles are trialed out using an Aerospace Distributed Design application, namely the design of an A340 wing box. The ontology of knowledge for agent-based Intelligent Distributed Mismatch Control System is introduced, as well as the distributed collaborative environment for consortium based projects

GRACE ontology integrating process and quality control

Multi-agent systems paradigm is a suitable approach to implement distributed manufacturing systems addressing the emergent requirements of flexibility, robustness and responsiveness. In such systems, an ontology is a crucial piece to provide a common understanding on the vocabulary used by the intelligent, distributed agents during the exchange of shared knowledge. This paper describes the design of an ontology to define the structure of the knowledge that is used within a multi-agent system integrating process and quality control in production lines for home appliances, which is being developed within the EU FP7 GRACE (inteGration of pRocess and quAlity Control using multi-agEnt technology) project. The ontology schema is validated by instantiating for a case study derived from a washing machines production line

Distributed communications and control network for robotic mining

The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed

Multi-agent system for integrating quality and process control in a home appliance production line

A current trend in manufacturing is the deployment of modular, distributed and intelligent control systems that introduce adaptation facing unexpected deviations and failures, namely in terms of production conditions and product demand fluctuation. The integration of quality and process control allows the implementation of dynamic self-adaptation procedures and feedback control loops to address a large variety of disturbances and changes in process parameters and variables, aiming to improve the production efficiency and the product quality. Multi-agent systems (MAS) technology (Wooldridge 2002)(Leitão et al. 2013) is suitable to face this challenge, offering an alternative way to design these adaptive systems, based on the decentralization of functions over distributed autonomous and cooperative agents, providing modularity, flexibility, adaptation and robustness. In spite of the potential benefits of the MAS technology, the number of deployed agent-based solutions in industrial environments, reported in the literature, are few, as illustrated in (Leitão et al. 2013) [colocar aqui referencia ao Pechoucek & Marik]. This chapter describes the development, installation and operation of a multi-agent system, designated as GRACE, integrating quality and process control to operate in a real home appliance production line, producing laundry washing machines, owned by Whirlpool and located in Naples, Italy. The use of the MAS technology acts as the intelligent and distributed infra-structure to support the implementation of real-time monitoring and feedback control loops that apply dynamic self-adaptation and optimization mechanisms to adjust the process and product variables. The agent-based solution was developed using the JADE (Java Agent DEvelopment Framework) framework and successfully installed in the industrial factory plant, contributing for demonstrating the effective applicability and benefits of the MAS technology, namely in terms of production efficiency and product quality.This work has been partly financed by the EU Commission, within the research contract GRACE coordinated by Univ. Politecnica delle Marche and having partners SINTEF, AEA srl, Instituto Politécnico de Bragança, Whirlpool Europe srl, Siemens AG.info:eu-repo/semantics/publishedVersio

Load control in low voltage level of the electricity grid using µCHP appliances

The introduction of microCHP (Combined Heat and Power) appliances and other means of distributed generation causes a shift in the way electricity is produced and consumed. Households themselves produce electricity and deliver the surplus to the grid. In this way, the distributed generation also has implications on the transformers and, thus, on the grid. In this work we study the influence of introducing microCHP appliances on the total load of a group of houses (behind the last transformer). If this load can be controlled, the transformer may be relieved from peak loads. Moreover, a well controlled fleet production can be offered as a Virtual Power Plant to the electricity grid.\ud \ud In this work we focus on different algorithms to control the fleet and produce a constant electricity output. We assume that produced electricity is consumed as locally as possible (preferably within the household). Produced heat can only be consumed locally. Additionally, heat can be stored in heat stores. Fleet control is achieved by using heat led control algorithms and by specifying as objective how much of the microCHP appliances have to run.\ud \ud First results show that preferred patterns can be produced by using fleet control. However, as the problem is heat driven, still reasonably large deviations from the objective occur. Several combinations of heat store and fleet control algorithm parameters are considered to match the heat demand and supply.\ud \ud This work is a first attempt in controlling a fleet and gives a starting point for further research in this area. A certain degree of control can already be established, but for better stability more intelligent algorithms are needed

A Combination of Workforce Sizing Plan and Worker Selection Guide with the Holonic Control Paradigm

The Holonic Workforce Allocation Model (HWM) is a dual-level advisory model using the concepts of Holonic Manufacturing Systems (HMS). The quantitative and pre-active level is termed as Workforce Sizing Plan (WOZIP), whereby the number of workers required for a production period can be forecasted. The resultant group of workers, in a case-by-case fashion, are continually assigned to parallel series of production tasks considering the individual skill and task urgency factors, at the qualitative and reactive level called Worker Selection Guide (WOSEG). When developing such an integrated model, four holonic control attributes need to be observed, namely real-time control, event-driven control, intelligent control, and distributed control. These control attributes help ensure the effective and sustainable improvement of factory processes, for which the strengths of and the interactions between holonic elements are discussed in this paper. Keywords: Holonic control, workforce sizing, worker selectio