Innovation landscape and challenges of smart technologies and systems - a European perspective

Latest developments in smart sensor and actuator technologies are expected to lead to a revolution in future manufacturing systems’ abilities and efficiency, often referred to as Industry 4.0. Smart technologies with higher degrees of autonomy will be essential to achieve the next breakthrough in both agility and productivity. However, the technologies will also bring substantial design and integration challenges and novelty risks to manufacturing businesses. The aim of this paper is to analyse the current landscape and to identify the challenges for introducing smart technologies into manufacturing systems in Europe. Expert knowledge from both industrial and academic practitioners in the field was extracted using an online survey. Feedback from a workshop was used to triangulate and extend the survey results. The findings indicate three main challenges for the ubiquitous implementation of smart technologies in manufacturing are: i) the perceived risk of novel technologies, ii) the complexity of integration, and iii) the consideration of human factors. Recommendations are made based on these findings to transform the landscape for smart manufacturing

Tuotannon dataintegraation virtaviivaistaminen

Industrial connectivity is lagging years behind consumer device connectivity. Both management and technological trends demand more data for decision making and one of the major hindrances is poor connectivity interfaces. Open Platform Communications Unified Architecture (OPC UA), a general industrial protocol for data transfer and information modelling, seeks to rise above first-party manufacturer data standards by providing a common way of implementation for industrial device connectivity. MTConnect, a free open-source data standard for mainly numerical control (NC) machine tools, seeks to do the same in the manufacturing industry. Can they both be used to ease the integration of devices in the comparable manner that Universal Plug and Play (UPnP) has successfully done for consumer devices? This thesis explores the differences of OPC UA and UPnP, the whys and how’s of manufacturing data collection focusing on NC machine tools from both management and technological perspectives, MTConnect and OPC UA capabilities, and finally seeks to answer the fore mentioned integration ease question. This pursuit is driven by global megatrends like Industry 4.0, Smart Manufacturing, Industrial Internet, Agile Manufacturing, Business Intelligence, Lean and JIT. As a part of this thesis, a prototype application using MTConnect and OPC UA is made to investigate if they have brought industrial data transfer standardization as far as UPnP has done in the consumer space. It was found that OPC UA and UPnP share many aspects technologically, but the differences are found in the depth and spread of standardization. Multi-device intercommunication is inherently a part of UPnP, but is something that has been largely neglected from OPC UA until 2015. The OPC UA - MTConnect companion specification allows easier integration of MTConnect devices into a factory-wide OPC UA network, but in a smaller environment MTConnect is easier to implement alone without OPC UA. The prototype proved that connectivity between OPC UA and MTConnect is effective albeit more time-consuming than implementing a mere MTConnect integration in a situation, where industrial devices are only outputting MTConnect data.Teollisen liitettävyyden standardointi on vuosia jälkijunassa verrattuna kuluttajalaitteiden liitettävyyteen. Niin hallinnolliset, kuin teknologisetkin trendit vaativat enemmän dataa päätöksentekoa varten ja tätä hidastaa eniten huonot liitettävyysrajapinnat. Open Platform Communications Unified Architecture (OPC UA) on teollisuuden yleisprotokolla, joka pyrkii nousemaan valmistajakohtaisten datastandardien yläpuolelle, tarjoten yhteisen toteutustavan teollisten laitteiden liitettävyyteen. MTConnect, ilmainen ja avoin numeerisesti ohjattujen työstökoneiden datastandardi pyrkii tekemään samoin valmistavassa teollisuudessa. Voiko näitä kahta yhdistää siten, että laitteiden integrointi helpottuu verrattavalla tavalla kuin Universal Plug and Play (UPnP) on onnistuneesti toteuttanut kuluttajalaitteiden kanssa? Tämä diplomityö tutkii miksi ja miten valmistavassa teollisuudessa kerätään dataa, keskittyen NC-koneisiin niin hallinnollisesta, kuin teknologisestakin näkökulmasta. Työssä tutkitaan MTConnect:n ja OPC UA:n mahdollisuuksia sekä pyritään vastaamaan edellä esitettyyn kysymykseen laitteiden integroinnista. Tätä pyrkimystä tukee maailman-laajuiset megatrendit kuten Industry 4.0, Smart Manufacturing, Industrial Internet, Agile Manufacturing, Business Intelligence, Lean ja JIT. Diplomityön osana tehdään prototyyppisovellus käyttäen MTConnect:a ja OPC UA:ta, jonka perusteella päätellään, ovatko nämä teollisten laitteiden datastandardointi tullut yhtä pitkälle kuin mitä UPnP kuluttajapuolella. Työssä havaittiin että OPC UA ja UPnP jakavat monia teknologisia osia ja että niiden eroavuudet löytyvät pääosin standardisoinnin syvyydestä ja kattavuudesta. Monen laitteen kanssa kommunikointi on sisäänrakennettua UPnP:ssä, kun taas OPC UA:sta tämä mahdollisuus on paljolti laiminlyöty vuoteen 2015 saakka. OPC UA:n ja MTConnect:n välinen kumppanispesifikaatio auttaa laitteiden integraatiota tehtaanlaajuisessa verkossa, mutta pienemmässä ympäristössä yksin MTConnectin käyttö on helpompaa. Tuloksista selvisi, että OPC UA:n ja MTConnect:n välinen liitettävyys on toimivaa, mutta enemmän aikaa vievää verrattuna pelkkään MTConnect-integraatioon tilanteessa, jossa teolliset laitteet käyttävät syöttävät vain MTConnect:n mukaista dataa

Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production

To achieve a highly agile and flexible production, it is envisioned that industrial production systems gradually become more decentralized, interconnected, and intelligent. Within this vision, production assets collaborate with each other, exhibiting a high degree of autonomy. Furthermore, knowledge about individual production assets is readily available throughout their entire life-cycles. To realize this vision, adequate use of information technology is required. Two commonly applied software paradigms in this context are Software Agents (referred to as Agents) and Digital Twins (DTs). This work presents a systematic comparison of Agents and DTs in industrial applications. The goal of the study is to determine the differences, similarities, and potential synergies between the two paradigms. The comparison is based on the purposes for which Agents and DTs are applied, the properties and capabilities exhibited by these software paradigms, and how they can be allocated within the Reference Architecture Model Industry 4.0. The comparison reveals that Agents are commonly employed in the collaborative planning and execution of production processes, while DTs typically play a more passive role in monitoring production resources and processing information. Although these observations imply characteristic sets of capabilities and properties for both Agents and DTs, a clear and definitive distinction between the two paradigms cannot be made. Instead, the analysis indicates that production assets utilizing a combination of Agents and DTs would demonstrate high degrees of intelligence, autonomy, sociability, and fidelity. To achieve this, further standardization is required, particularly in the field of DTs.Comment: Manuscript submitted to Journal of Intelligent Manufacturing, Corresponding dataset: https://doi.org/10.5281/zenodo.8120623 Additional references in Sec. 1, some other minor change

Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches