Borja Ramis Ferrer

Cyber–Physical Systems for Open-Knowledge-Driven Manufacturing Execution Systems

Manufacturing execution systems play an important role of bridging high-level enterprise functions and production or manufacturing operations. The embedded systems are usually in charge of controlling execution of the operations. Modern embedded systems have become capable of simultaneous and deterministic execution of control algorithms and IP-based communication, making it possible to create complex cyber-physical systems (CPSs), where the computational and communication resources of a device can be used directly for various control, supervisory, or monitoring functions. The complexity for defining open-knowledge-driven manufacturing execution system (OKD-MES) is in maintaining awareness of overall system state to avoid disruptive actions as various functions may be requested from a system. The problem is that obtaining such information on system state may necessitate collecting data from a number of devices, as there may not be a single data point for state information. This paper describes and illustrates an approach for designing OKD-MES on top of CPSs that controls robot workstations and conveyor-based transportation system of a pallet-based production system.

An approach for knowledge-driven product, process and resource mappings for assembly automation

The rapid development and reconfiguration of assembly automation systems to accommodate product changes in a short period of time is a challenging task due to the limitations of the contemporary automation systems engineering approach. To improve the engineering process, Product Process Resource (PPR)-based modeling, simulation and data integration systems emerged as a promising approach to compress the development time and engineering cost by enabling collaboration and realization of product and manufacturing resources in a virtual environment. However, due to ineffective coupling of PPR data, design and reconfiguration of assembly systems is still a challenging task and is highly dependent on the knowledge and experience of engineers. This paper presents a knowledge-driven engineering approach to manage the mapping of engineering data sets to interconnect product attributes to manufacturing process and resources. A case study based on a Festo test rig is presented for illustrating the implementation of the approach. The successful identification of the tasks required to manufacture a product proves the approach concept but only for the presented use case.

Management of distributed knowledge encapsulated in embedded devices

Embedded electronic devices are now to be found everywhere. In general, they can be used to collect different sorts of data (e.g. on temperature, humidity, illumination and locations). In some specific domains, such as industrial automation, embedded devices are used for process control. The devices may have a programme that can respond immediately to environmental changes perceived through sensors. In the control of large sites, where there are many devices, higher level decisions are made or processed in dedicated computers far away from the sources (devices) where the initial data are collected. This article shows how it is possible to manage portions of distributed knowledge, hosted in embedded devices, making it possible for each embedded device to hold and manage its piece of knowledge. In addition, presented approach allows keeping locus of control at the embedded device level, where the embedded device can make decisions knowing the status of the rest of the world, device contributions and their effects in the overall distributed system knowledge base.

A knowledge-based solution for automatic mapping in component based automation systems

Due to the current business requirements, the manufacturing industry is striving to reduce design, development and commissioning time of production systems to manufacture new products in a timely manner. The use of new technologies such as virtual engineering, automatic code generation and knowledge-based approaches is being extensively researched. This paper presents a framework that utilizes a knowledge-based approach to automate the component mapping in the code generation process. The raw data is taken from simulation models of manufacturing systems developed in 3D based virtual engineering tools. Moreover, a prototype implementation is presented and the results are discussed.

Product, process and resource model coupling for knowledge-driven assembly automation

Abstract Accommodating frequent product changes in a short period of time is a challenging task due to limitations of the contemporary engineering approach to design, build and reconfigure automation systems. In particular, the growing quantity and diversity of manufacturing information, and the increasing need to exchange and reuse this information in an efficient way has become a bottleneck. To improve the engineering process, digital manufacturing and Product, Process and Resource (PPR) modelling are considered very promising to compress development time and engineering cost by enabling efficient design and reconfiguration of manufacturing resources. However, due to ineffective coupling of PPR data, design and reconfiguration of assembly systems are still challenging tasks due to the dependency on the knowledge and experience of engineers. This paper presents an approach for data models integration that can be employed for coupling the PPR domain models for matching the requirements of products for assembly automation. The approach presented in this paper can be used effectively to link data models from various engineering domains and engineering tools. For proof of concept, an example implementation of the approach for modelling and integration of PPR for a Festo test rig is presented as a case study.

Private local automation clouds built by CPS

The employment of cyber-physical systems allows the control of processes in modern production lines. On the other hand, several research works have recently presented how ontology-based knowledge representation can be a suitable method for modelling industrial systems. However, system models are located far away from where the data is generated which adds complexity for cross-domain communications and resource management. Current embedded devices can encapsulate ontological models that can be accessed as local resources. This article presents the integration of interconnected devices as the computational nodes of a cloud which is private and local. In this way, functionalities, such as knowledge management and process control can be performed closer to the industrial equipment. Moreover, this research work discusses the potential and challenges for performing distributed reasoning in the private local automation cloud. In addition, the article describes main aspects of the system architecture and the behaviour of the networked embedded devices in the cloud. The research work results will be used as a high-level roadmap for further system implementation.

A web-based simulator for a discrete manufacturing system

Virtualization has become a supportive approach for simulating system behaviour efficiently thanks to the revolution of computer and smart devices. In fact, the employment of running virtual tools that mimic the real physical world is nowadays a requirement in some fields as in e.g. industrial automation. This research work presents a virtual tool that simulates a real assembly line. The main features of this simulator are listed as; web application that can be accessed with any devices that supports html web pages, animated application that provides a UI for the user, discovery mechanism that allows web applications to interact with the simulator automatically and RESTful-based services, which increases the flexibility and versatility in terms of deployment. FASTory simulator has been developed and deployed during the eScop project. In addition, presented simulator has been employed by C2NET (Cloud Collaborative Manufacturing Networks) project for development some of its tools. Furthermore, the exploitation of the FASTory simulator is extended to cover as well the education of next generation of engineers for design and implementation of modern CPS. As Tampere University of Technology provides a M.Sc. degree in automation engineering, students use the simulator for their experiments, ensuring that mistakes are recoverable and harmless.

Generic platform for manufacturing execution system functions in knowledge-driven manufacturing systems

ABSTRACT Information technologies grow rapidly nowadays with the advance and extension of computing capabilities. This growth affects several fields, which consume these technologies. Industrial Automation is not an exception. This publication describes a general and flexible architecture for implementing Manufacturing Execution System (MES) function, which can be deployed in multiple industrial cases. These features are achieved by combining the flexibility of knowledge-driven systems with the vendor-independent property of RESTful web services. With deployment of this solution, MES functions may gain more versatility and independency. This research work is a continuation of the development of the OKD-MES (Open Knowledge-Driven Manufacturing Execution System) framework during the execution of the eScop project. The OKD-MES framework consists on a semantic-based solution for controlling and enhancing the flexibility and re-configurability of MES. In such scope, this research presents MES functions architecture that might be implemented in the OKD-MES framework in order to increase the flexibility of event-driven manufacturing systems.

An approach for integrating legacy systems in the manufacturing industry

The objective of the Cloud Collaborative Manufacturing Networks (C2NET) project is the development of a cloud-based platform that will allow an efficient collaboration and optimization of supply chain processes. One of the main components of the C2NET platform is the Data Collection Framework (DCF) and the Data Collection Client (DCC), which must provide a reliable solution for receiving data from heterogeneous data sources. Moreover, incoming data must be transformed in a way that can be presented in the required format to be handled by optimizer and collaboration tools that reside in the C2NET platform. This research work focuses on the collection of data from different legacy systems. Then, this article presents an approach that may be employed by C2NET to permit the DCC to receive, interpret and transform data. Presented approach uses the PLANTCockpit OS solution, which principles and functionality are also included in the manuscript.

Towards the encapsulation and decentralisation of OKD-MES services within embedded devices

Traditionally, the resources of embedded devices which are employed for process control at shop floors were resource constrained. However, advances in embedded system technologies permit the enhancement of the processing and storage capabilities of embedded devices. Therefore, semantic descriptions of manufacturing systems can now be hosted and computed at the device level. This fact permits the creation of a decentralised solution for controlling processes at the lowest level of the manufacturing enterprises and the reduction in the time and effort requirements for the configuration and information exchange. The eScop project presented the Open Knowledge-Driven Manufacturing Execution System (OKD-MES) solution, which enables monitoring and controlling production systems openly and allows runtime re-configurability of interconnected industrial equipment and services. This research work presents how part of the OKD-MES functionality can be handled at lower level. More precisely, the OKD-MES representation and management of knowledge can be decentralised and handled at the shop floor level, where the industrial machines are connected to devices that are capable of controlling the execution of processes. The main objective of this paper is to describe a decentralised vision for the OKD-MES framework, which is a centric solution in terms of knowledge management. Moreover, the article also discusses some of the advantages to be gained from decentralising the management of knowledge model semantic descriptions.