Synchro-push: A new production control paradigm

The paper aims at proposing a new production control paradigm, the Synchro-push, that offers a step forward with respect to the traditional push and pull production paradigms as for plant re-configurability power and quick reaction to demand changes: in fact, theoretically, it offers the advantages of the two traditional approaches without suffering their drawbacks. This could be of advantage for any manufacturing company and especially for SMEs (Small-Medium Enterprises), acting as a support against worldwide competition. The paper presents a brief history of the evolution of the push and pull approaches, the comparison between them and among the different alternatives that have been proposed in literature for their implementation. It presents the new approach, its theory and the subsequent industrial implications. The new approach is now made possible by the development of innovative smart technologies that allow the close-to-real-time decision making in scheduling and a higher level of modularity in the plant

Cloud manufacturing as a sustainable process manufacturing route

Cloud Manufacturing (CM) is a service oriented business model to share manufacturing capabilities and resources on a cloud platform. Manufacturing is under pressure to achieve cost and environmental impact reductions, as manufacturing becomes more integrated and complex. Cloud manufacturing offers a solution, as it is capable of making intelligent decisions to provide the most sustainable and robust manufacturing route available. Although CM research has progressed, a consensus is still lacking on the concepts within CM as well as applications and scope beyond discrete manufacturing. The aim of this paper is to demonstrate how CM offers a more sustainable manufacturing future to the industry as a whole, before focusing specifically on the application to process manufacturing (e.g. food, pharmaceuticals and chemicals). This paper details the definitions, characteristics, architectures and previous case studies on CM. From this, the fundamental aspects of the CM concept are identified, along with an analysis of how the concept has progressed. A new, comprehensive CM definition is formulated by combining key concepts drawn from previous definitions and emphasizes CM potential for sustainable manufacturing. Four key methods of how CM increases sustainability are identified: (1) collaborative design; (2) greater automation; (3) improved process resilience and (4) enhanced waste reduction, reuse and recovery. The first two key methods are common to both discrete and process manufacturing, however key methods (3) and (4) are more process manufacturing specific and application of CM for these has yet to be fully realised. Examples of how CM’s characteristics may be utilised to solve various process manufacturing problems are presented to demonstrate the applications of CM to process manufacturing. Waste is an important consideration in manufacturing, with strong sustainability implications. The current focus has been on using CM for waste minimisation; however, process manufacturing offers waste as a resource (valorisation opportunities from diversifying co-products, reuse, recycle and energy recovery). Exploring CM’s potential to characterise and evaluate alternative process routes for the valorisation of process manufacturing waste is considered for the first time. The specific limitations preventing CM adoption by process manufacturers are discussed. Finally, CM’s place in the future of manufacturing is explored, including how it will interact with, and complement other emerging manufacturing technologies to deliver a circular economy and personalised products

Semantic modelling for dynamic system recognition in non-intrusive industrial monitoring systems

Industrial monitoring systems play important role in decision making on all levels of a factory from the shop floor to ERP systems influencing overall efficiency of production. Together with a trend for mass customization and constantly increasing tempo of introduction of new products, equipment and technologies to manufacturing, contemporary monitoring systems should provide enough flexibility to be up to date with manufacturing system. Such monitoring systems as the one offered in European Commission project PLANTCockpit, offer the approach of extensively reconfigurable, loosely coupled systems. Unfortunately, configuration of the monitoring system which could work on all levels of automation hierarchy requires the knowledge of all those levels together with knowledge of integration technologies and tedious work related with creation of configuration itself. Present thesis work offers an approach which automates the configuration process employing knowledge bases. This approach includes employment of SOA on device level, with semantically enhanced services descriptions (and possibility to employ the gateway devices for non-intrusiveness), definition of the metrics to be monitored by the system in the knowledge base, as well as set of algorithms and standards required to create configuration of the monitoring system. Reusability of knowledge defined on devices and in knowledge base simplifies the process of introduction of new devices, metrics or other reconfiguration of the monitoring system. The system implementing proposed approach has been developed in this thesis and was able to configure monitoring system for a test bed

An Integrated Approach for Ontology-Driven Configuration Management and Run-Time Execution of Manufacturing Systems

The contemporary manufacturing systems must respond instantly to rapidly changing customer and market requirements in order to survive the intensive competitive environment. The factories should have the agility to adapt to mass customization and introduction of new product, equipment and technology to manufacturing. This is possible by having re-configurable loosely coupled system which offers run-time decision making capability on all levels of factory from shop floor to ERP systems. This thesis proposes a knowledge-based approach for achieving shop-floor device configuration management, run-time execution support for orchestration engines and re-configurable visualization for monitoring systems. The thesis work was carried out as a part of the European project eScop by Arthemis Joint Undertaking, where knowledge bases as the information source for manufacturing execution system is the core concept. This thesis work involves semantic modeling of the manufacturing knowledge in a Manufacturing System Ontology (MSO) and exposing the knowledge to other components of the system using web services. It employs Service Oriented Architecture (SOA) on device level to facilitate knowledge extraction. A methodology is put forward in the thesis to design ontology with broader capabilities and queries for reasoning the ontology. Ontologies are extendable and easy to update offering flexibility to address system changes. The reusability of knowledge simplifies the addition of new product or equipment and thereby offering re-configurability to the system. The proposed approach has been tested by implementing on a real manufacturing system and the research objectives were achieved

A Semantically Enhanced Approach for Orchestration of Web Services in Factory Automation Systems

The Service-oriented Architecture (SOA) paradigm makes it possible to build systems from several independent components. Most typically, web services are chosen as the building blocks of such a system. A web service is essentially a passive software entity, which listens for request messages sent to it over the network, possibly reacts to the requests by performing some operations, and finally sends response messages to the request senders. The traditional application domain of web services belongs to the so-called IT domain. While opening new horizons in software development life-cycles, web services have been adopted in various new application domains, including the domain of factory automation (software development for factory automation). Indeed, recent research projects have experimented with controlling production system equipment through web service interfaces. When migrated from pure software to the physical realm involving industrial equipment, web services set additional demands for the application domains. For example, since the domains involve operations with physical effects, roll-back or application recovery procedures become challenging. This research work targets the orchestration of factory automation systems encapsulated as web services and presents various techniques for overcoming the difficulties. Orchestrating web services to accomplish a complicated production task can be difficult due to the transitoriness of both production equipment states and the set of available web services. Nevertheless, the selection of appropriate web services can be facilitated by augmenting each service with semantic information describing its conditions and effects. Web services augmented with such descriptions are termed semantic web services. While Web Ontology Language, OWL, is ideal for describing application domain concepts and property relationships, the OWL-S ontology, which is based on OWL, has been specifically developed for describing web services. Once the semantic service descriptions have been analyzed to find the appropriate web services, the selected services can be invoked using their syntactic WSDL descriptions. In addition to automated web service selection, semantic descriptions allow the composition of web services to achieve production tasks. Service composition involves first analyzing the descriptions to determine the appropriate service invocation process for achieving the desired goal and then executing the process. This dissertation presents an approach in which the production equipment and their states are represented using an ontology, and the model is dynamically used in decision-making. In particular, the devices in the considered production systems provide web service interfaces through which they can be controlled, while semantic web service descriptions formulated in OWL-S make it possible to determine the conditions and effects of invoking the web services. The approach presented in this research work additionally involves a set of specialized web services that co-operate to achieve production goals using the domain web services. One of the services maintains a semantic model of the current system state, while another uses the model to compose the domain web services so that they jointly achieve the desired goals. The semantic model of the system is automatically updated based on event notifications sent by the domain services. Software agents controlling production devices must maintain an up-to-date view of the physical world state in order to efficiently reason and plan their actions. Especially in a factory automation system, the world state undergoes rapid evolution, and the world view must remain synchronized with the changes. This research discusses two approaches to updating the world view based on event notifications sent by web services representing production devices in a manufacturing system. One of the approaches is based on separately specified update rules, and one automatically uses semantic web service descriptions formulated in OWL-S. While all of the examples presented in this research work specifically focus on the factory automation domain, the presented approaches are applicable to all domains involving semantic web services. Semantic Web Service descriptions facilitate the automated discovery and composition of web services. Particularly in the production system domain, the service condition and effect descriptions are essential in selecting the appropriate service or service composition for a given task. OWL-S is one of the most popular semantic web service description languages, and due to its XML syntax, OWL-S can be effortlessly incorporated into service WSDL descriptions. However, developing OWL-S documents for each service instance is laborious. This dissertation presents an approach to automatically generating executable OWL-S descriptions from semantically annotated service WSDL files. Computing clouds facilitate rapid and effortless resource allocation. Cloud consumers can generally be ignorant of the physical computing resources used or their geographical location, as the resources are abstracted into a commodity that can be dynamically leased from the cloud provider. In particular, Infrastructure-as-a-Service clouds allow clients to dynamically lease virtual machines that behave similarly to physical servers. However, executing an application by directly using computing cloud resources is complicated and typically involves similar steps as installing and executing an application on a physical machine. Moreover, starting numerous application instances on a single virtual machine may result in poor performance. Thus, this dissertation considers the development of a web service that facilitates the use of cloud resources by abstracting them. When the web service is used, an application can be effortlessly started in a computing cloud by invoking simple web service operations. Furthermore, when multiple applications are started, the workload can be automatically distributed between several virtual machines, resulting in higher performance. To conclude, the results presented in this research work demonstrate that semantic web service descriptions can indeed facilitate automatic web service composition and invocation. However, the effort of developing semantic web service descriptions can partly undermine the benefits achieved through their application. Therefore, new tools and methods should be developed to minimize the effort of developing such descriptions

An Approach to Automatically Distribute and Access Knowledge within Networked Embedded Systems in Factory Automation

This thesis presents a novel approach for automatically distribute and access knowledge within factory automation systems built by networked embedded systems. Developments on information, communication and computational technologies are making possible the distribution of tasks within different control resources, resources which are networked and working towards a common objective optimizing desired parameters. A fundamental task for introducing autonomy to these systems, is the option for represent knowledge, distributed within the automation network and to ensure its access by providing access mechanisms. This research work focuses on the processes for automatically distribute and access the knowledge.Recently, the industrial world has embraced service-oriented as architectural (SOA) patterns for relaxing the software integration costs of factory automation systems. This pattern defines a services provider offering a particular functionality, and service requesters which are entities looking for getting their needs satisfied. Currently, there are a few technologies allowing to implement a SOA solution, among those, Web Technologies are gaining special attention for their solid presence in other application fields. Providers and services using Web technologies for expressing their needs and skills are called Web Services. One of the main advantage of services is the no need for the service requester to know how the service provider is accomplishing the functionality or where the execution of the service is taking place. This benefit is recently stressed by the irruption of Cloud Computing, allowing the execution of certain process by the cloud resources.The caption of human knowledge and the representation of that knowledge in a machine interpretable manner has been an interesting research topic for the last decades. A well stablished mechanism for the representation of knowledge is the utilization of Ontologies. This mechanism allows machines to access that knowledge and use reasoning engines in order to create reasoning machines. The presence of a knowledge base allows as clearly the better identification of the web services, which is achievable by adding semantic notations to the service descriptors. The resulting services are called semantic web services.With the latest advances on computational resources, system can be built by a large number of constrained devices, yet easily connected, building a network of computational nodes, nodes that will be dedicated to execute control and communication tasks for the systems. These tasks are commanded by high level commanding systems, such as Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP) modules. The aforementioned technologies allow a vertical approach for communicating commanding options from MES and ERP directly to the control nodes. This scenario allows to break down monolithic MES systems into small distributed functionalities, if these functionalities use Web standards for interacting and a knowledge base as main input for information, then we are arriving to the concept of Open KnowledgeDriven MES Systems (OKD-MES).The automatic distribution of the knowledge base in an OKD-MES mechanism and the accomplishment of the reasoning process in a distributed manner are the main objectives for this research. Thus, this research work describes the decentralization and management of knowledge descriptions which are currently handled by the Representation Layer (RPL) of the OKD-MES framework. This is achieved within the encapsulation of ontology modules which may be integrated by a distributed reasoning process on incoming requests. Furthermore, this dissertation presents the concept, principles and architecture for implementing Private Local Automation Clouds (PLACs), built by CPS.The thesis is an article thesis and is composed by 9 original and referred articles and supported by 7 other articles presented by the author