Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Open Platform Concept for Blockchain- Enabled Crowdsourcing of Technology Development and Supply Chains

We outline the concept of an open technology platform which builds upon a publicly accessible library of fluidic designs, manufacturing processes and experimental characterisation, as well as virtualisation by a ‘digital twin” based on modelling, simulation and cloud computing. Backed by the rapidly emerging Web3 technology “Blockchain”, we significantly extend traditional approaches to effectively incentivise broader participation by an interdisciplinary ‘value network’ of diverse players. Ranging from skilled individuals (the ‘citizen scientist’, the ‘garage entrepreneur’) and more established research institutions to companies with their infrastructures, equipment and services, the novel platform approach enables all stakeholders to jointly contribute to value creation along more decentralised supply chain designs including research and technology development (RTD). Blockchain-enabled “Wisdom of the Crowds” and “Skin in the game” mechanisms secure “trust” and transparency between participants. Prediction markets are created for guiding decision making, planning and allocation of funding; competitive parallelisation of work and its validation from independent participants substantially enhances quality, credibility and speed of project outcomes in the real world along the entire path from RTD, fabrication and testing to eventual commercialisation. This novel, Blockchain-backed open platform concept can be led by a corporation, academic entity, a loosely organised group, or even “chieflessly” within a smart-contract encoded Decentralised Autonomous Organisation (DAO). The proposed strategy is particularly attractive for highly interdisciplinary fields like Lab-on-a- Chip systems in the context of manifold applications in the Life Sciences. As an exemplar, we outline the centrifugal microfluidic “Lab-on-a-Disc” technology. Rather than engaging in all sub-disciplines themselves, many smaller, highly innovative actors can focus on strengthening the product component distinguishing their unique selling point (USP), e.g., a particular bioassay, detection scheme or application scenario. In this effort, system integrators access underlying commons like fluidic design, manufacture, instrumentation and software from a more resilient and diversified supply chain, e.g., based on a verified pool of community-endorsed or certified providers

Blockchain smart contracts: Applications, challenges, and future trends

In recent years, the rapid development of blockchain technology and cryptocurrencies has influenced the financial industry by creating a new crypto-economy. Then, next-generation decentralized applications without involving a trusted third-party have emerged thanks to the appearance of smart contracts, which are computer protocols designed to facilitate, verify, and enforce automatically the negotiation and agreement among multiple untrustworthy parties. Despite the bright side of smart contracts, several concerns continue to undermine their adoption, such as security threats, vulnerabilities, and legal issues. In this paper, we present a comprehensive survey of blockchain-enabled smart contracts from both technical and usage points of view. To do so, we present a taxonomy of existing blockchain-enabled smart contract solutions, categorize the included research papers, and discuss the existing smart contract-based studies. Based on the findings from the survey, we identify a set of challenges and open issues that need to be addressed in future studies. Finally, we identify future trends

ENHANCING THE OPERATIONAL RESILIENCE OF CYBER- MANUFACTURING SYSTEMS (CMS) AGAINST CYBER-ATTACKS

Cyber-manufacturing systems (CMS) are interconnected production environments comprised of complex and networked cyber-physical systems (CPS) that can be instantiated across one or many locations. However, this vision of manufacturing environments ushers in the challenge of addressing new security threats to production systems that still contain traditional closed legacy elements. The widespread adoption of CMS has come with a dramatic increase in successful cyber-attacks. With a myriad of new targets and vulnerabilities, hackers have been able to cause significant economic losses by disrupting manufacturing operations, reducing outgoing product quality, and altering product designs. This research aims to contribute to the design of more resilient cyber-manufacturing systems. Traditional cybersecurity mechanisms focus on preventing the occurrence of cyber-attacks, improving the accuracy of detection, and increasing the speed of recovery. More often neglected is addressing how to respond to a successful attack during the time from the attack onset until the system recovery. We propose a novel approach that correlates the state of production and the timing of the attack to predict the effect on the manufacturing key performance indicators. Then a real-time decision strategy is deployed to select the appropriate response to maintain availability, utilization efficiency, and a quality ratio above degradation thresholds until recovery. Our goal is to demonstrate that the operational resilience of CMS can be enhanced such that the system will be able to withstand the advent of cyber-attacks while remaining operationally resilient. This research presents a novel framework to enhance the operational resilience of cyber-manufacturing systems against cyber-attacks. In contrast to other CPS where the general goal of operational resilience is to maintain a certain target level of availability, we propose a manufacturing-centric approach in which we utilize production key performance indicators as targets. This way we adopt a decision-making process for security in a way that is aligned with the operational strategy and bound to the socio-economic constraints inherent to manufacturing. Our proposed framework consists of four steps: 1) Identify: map CMS production goals, vulnerabilities, and resilience-enhancing mechanisms; 2) Establish: set targets of performance in production output, scrap rate, and downtime at different states; 3) Select: determine which mechanisms are needed and their triggering strategy, and 4) Deploy: integrate into the operation of the CMS the selected mechanisms, threat severity evaluation, and activation strategy. Lastly, we demonstrate via experimentation on a CMS testbed that this framework can effectively enhance the operational resilience of a CMS against a known cyber-attack

The positive impacts of Real-World Data on the challenges facing the evolution of biopharma.

Demand for healthcare services is unprecedented. Society is struggling to afford the cost. Pricing of biopharmaceutical products is under scrutiny, especially by payers and Health Technology Assessment agencies. As we discuss here, rapidly advancing technologies, such as Real-World Data (RWD), are being utilized to increase understanding of disease. RWD, when captured and analyzed, produces the Real-World Evidence (RWE) that underpins the economic case for innovative medicines. Furthermore, RWD can inform the understanding of disease, help identify new therapeutic intervention points, and improve the efficiency of research and development (R&D), especially clinical trials. Pursuing precompetitive collaborations to define shared requirements for the use of RWD would equip service-providers with the specifications needed to implement cloud-based solutions for RWD acquisition, management and analysis. Only this approach would deliver cost-effective solutions to an industry-wide problem

The application of digital twin technology in operations and supply chain management: a bibliometric review

Purpose The application of digital twins to optimise operations and supply chain management functions is a bourgeoning practice. Scholars have attempted to keep pace with this development initiating a fast-evolving research agenda. The purpose of this paper is to take stock of the emerging research stream identifying trends and capture the value potential of digital twins to the field of operations and supply chain management. Design/methodology/approach In this work we employ a bibliometric literature review supported by bibliographic coupling and keyword co-occurrence network analysis to examine current trends in the research field regarding the value-added potential of digital twin in operations and supply chain management. Findings The main findings of this work are the identification of four value clusters and one enabler cluster. Value clusters are comprised of articles that describe how the application of digital twin can enhance supply chain activities at the level of business processes as well as the level of supply chain capabilities. Value clusters of production flow management and product development operate at the business processes level and are maturing communities. The supply chain resilience and risk management value cluster operates at the capability level, it is just emerging, and is positioned at the periphery of the main network. Originality/value This is the first study that attempts to conceptualise digital twin as a dynamic capability and employs bibliometric and network analysis on the research stream of digital twin in operations and supply chain management to capture evolutionary trends, literature communities and value-creation dynamics in a digital-twin-enabled supply chain

Transforming healthcare with the synergy of biotechnology and information technology

We explore the integration of biotechnology and information technology in healthcare innovation. The convergence of these fields has revolutionized diagnostics, therapeutics and patient management. Biotechnology advancements, such as genomics and molecular diagnostics, enable personalized medicine, while information technology facilitates data management and analysis. The integration also extends healthcare access through telemedicine and remote patient monitoring, enhancing healthcare delivery in underserved areas. Challenges include data security and privacy concerns. Looking ahead, the integration of biotechnology and information technology holds immense potential for further healthcare innovation, transforming patient outcomes and healthcare delivery

A Design Science Research Approach to Architecting and Developing Information Systems for Collaborative Manufacturing : A Case for Human-Robot Collaboration

Konseptointi- ja suunnitteluvaiheessa sekä valmistuksen, käytön ja kehitysprosessin aikana syntyy tietoa, jonka hyödyntämisessä on valtavaa potentiaalia liike-elämän ja tuotantoprosessien muuttamiseen. Neljännen teollisen vallankumouksen ytimessä oleva digitaalinen muutos tunnistaa tämän painottaen erityisesti tämän tiedon yhdistämistä toimintojen ja järjestelmien tukemiseksi läpi tuotteen elinkaareen, mitä kutsutaan digitaaliseksi säikeen kehykseksi (digital thread framework). Tämän väitöskirjan tavoitteena on kehittää ja käyttää yhtä tällaista viitekehystä ihmisen ja robotin yhteistoiminnan asiayhteydessä. Tämä kehys pyrkii vastaamaan merkittävään ongelmaan, joka liittyy mukautuvuuden ja joustavuuden abstrakteihin ominaisuuksiin. Nykyiset ihmisen ja robotin yhteistyöjärjestelmät (human-robot collaboration (HRC)) on rakennettu pääasiassa pysyviksi järjestelmiksi, jotka sivuuttavat ihmisten intuitiivisen toiminnan asettamalla heidän roolinsa yhteistyötehtävissä etukäteen määritellyiksi. Lisäksi järjestelmien kyky vaihtaa tuotteesta toiseen on rajoittunutta. Tämä on erityisen ongelmallista nykyisellä laajan tuotevalikoiman aikakaudella, joka johtuu asiakkaiden räätälöidyistä vaatimuksista. Tähän taustaan vastaten, tämä väitöskirja käyttää design science research methodology -menetelmää suunnitellakseen, kehittääkseen ja ottaakseen käyttöön kolme pääasiallista artefaktia ihmisen ja robotin yhteistyösolussa laboratorioympäristössä. Ensimmäinen on digitaalisen säikeen kehys (digital thread framework), joka integroi tuotesuunnitteluympäristön toimijaksi monitoimijajärjestelmään käyttäen uusimpia tietoon perustuvia suunnittelujärjestelmiä, mikä tarjoaa prosessin toimijoille pääsyn tuotesuunnittelumalleihin reaaliajassa. Toinen on lisätyn todellisuuden malli, joka tarjoaa rajapinnan kokoonpanotehtävässä yhteistyöhön osallistuvan ihmisoperaattorin ja edellä mainitun kehyksen välille. Kolmas on tukitietomalli, jota yhteistyötä tekevät toimijat käyttävät tietopohjanaan täyttääkseen yhteistyössä tapahtuvan kokoonpanon tavoitteet mukautuvasti. Näitä kehitettyjä artefakteja käytettiin kokonaisuutena tapaustutkimuksissa, jotka liittyivät aidon dieselmoottorin kokoonpanoon, ja joissa todennettiin niiden hyödyllisyys ja että ne lisäävät joustavuutta, jota varten kehys (framework) suunniteltiin. Rajauslaatikoiden näyttäminen skaalautuvana informaationa, joka hahmottaa alikokoonpanon osien geometriaa, demostroi kehitettyjen artefaktien käytettävyyttä yhteistyötä tekevien toimijoiden aikomuksia heijastavien laajennetun todellisuuden projektioiden tuottamiseksi. Yhteenvetona tämän väitöskirjan tuloksena syntyi lähestymistapa älykkään ja mukautuvan robotiikan toteuttamiseksi hyödyntäen tietovirtoja ja mallinnusta ihmisen ja robotin yhteistoiminnan kontekstissa. Teollisuuden raportoima älykkäästi mukautuvien HRC-järjestelmien puute taas toimi osaltaan motivaationa tähän väitöskirjassa tehtyyn työhön. Kun tulevaisuuden tuotteet ja tuotantojärjestelmät muuttuvat monimutkaisemmiksi, tietojärjestelmiltä odotetaan suurempaa vastuuta korvaamaan ihmisen työmuistin luontaiset rajat ja mahdollistamaan siirtyminen kohti ihmiskeskeistä valmistusta, joihin viitataan termeillä Operator 4.0 ja Industry 5.0. Näin ollen on odotettavissa, että tietojärjestelmien tutkimus, kuten tämä väitöskirja, voi auttaa ottamaan merkittäviä askeleita tähän suuntaan.Information generated from the conceptualization, design, manufacturing, and use of a product has immense potential in transforming both the business and manufacturing processes of the manufacturing enterprise. The digital transformation at the heart of the fourth industrial revolution has acknowledged this with a special emphasis on weaving a thread of this information to support functions and systems throughout the life cycle of the product with what is known as a digital thread framework. This dissertation aims to develop and use one such framework in the context of human-robot collaborative assembly. The overarching problem that the framework aims to solve can be attributed to the abstract qualities of adaptability and flexibility. The human-robot collaboration (HRC) systems of today are built predominantly as static systems and ignore the intuitive role of humans by having their roles in collaborative tasks pre-defined. Furthermore, their ability to switch between products during product changeovers is also limited. This is especially problematic in the current era of product variety, stemming from the customised requirements of customers. To this end, this dissertation employs the design science research methodology to design, develop, and deploy predominantly three artefacts in a human-robot work cell in a laboratory setting. The first is the digital thread framework that integrates the product design environment using state-of-the-art knowledge-based engineering systems, as an agent of a multi-agent system, which provide the collaborative human-robot agents with access to product design models at run time. The second is a constituent mixed-reality model that provides an interface for the foregoing framework for the human operator engaged in collaborative assembly. The third is a supporting information model that the agents use as their knowledge base to fulfil adaptively the goals of collaborative assembly. Together, these developed artefacts were employed in case studies involving a real diesel engine assembly during which they were observed to provide utility and support the cause of adaptability for which the framework was designed. The identification of bounding boxes as a scalable information construct, that approximates the part geometry of the sub-assembly components, demonstrates the utility of the developed artefacts for spatially augmenting them as projections as intentions of collaborating agents. In summary, this dissertation contributes with an approach towards realising intelligent and adaptive robotics within the realms of information flows and modelling in the context of human-robot collaboration. The lack of intelligently adaptable HRC systems reported by the industry in part motivated the work undertaken in this dissertation. As future products and production systems become more complex, information systems are expected to assume greater responsibility to compensate for the inherent limits of the human working memory and enable transition towards a human-centred manufacturing, the current likes of which are labelled as Operator 4.0 and Industry 5.0. Thus, the expectation is that information systems research, such as this dissertation, can help take significant strides forward in this direction

Lift 2020 Spring

https://commons.erau.edu/lift-magazine/1035/thumbnail.jp