Towards a conceptual model of structural and behavioral elements in cyber-physical production systems

9th 9th IFAC IFAC Conference Conference on on Manufacturing Manufacturing Modelling, Modelling, Management Management and and Control 9th IFAC Conference on Manufacturing Modelling, Management and Available online at www.sciencedirect.com Control 9th IFAC Conference on Manufacturing Modelling, Management Control Berlin, Germany, August 28-30, 2019 9th IFAC Conference on Manufacturing Modelling, Management and and Berlin, Germany, August 28-30, 2019 Control Berlin, ControlGermany, August 28-30, 2019 Berlin, Berlin, Germany, Germany, August August 28-30, 28-30, 2019 2019

ScienceDirect

IFAC PapersOnLine 52-13 (2019) 863–868

Towards a conceptual model of structural and behavioral elements in cyberTowards Towards aa conceptual conceptual model model of of structural structural and and behavioral behavioral elements elements in in cybercyberphysical production systems Towards and behavioral elements in cyberof structural physical production systems Towards aa conceptual conceptual model model of structural and behavioral elements in cyberphysical production systems physical production systems physical production systems Thiago Regal*, Carlos Eduardo Pereira*

Thiago Thiago Regal*, Regal*, Carlos Carlos Eduardo Eduardo Pereira* Pereira* Thiago Regal*, Carlos Eduardo Pereira* Thiago Regal*, Carlos Eduardo Pereira* ** Electrical Engineering Department, Universidade Federal do Rio Rio Grande do do Sul, Electrical Engineering Department, Universidade Federal do * Electrical Engineering Department, Universidade Federal do Rio Grande Grande do Sul, Sul, Porto Alegre, Brazil, (e-mail: [email protected], [email protected]) Porto Brazil, [email protected], [email protected]) ** Electrical Engineering Department, Universidade do Electrical Engineering Department, Universidade Federal Federal do Rio Rio Grande Grande do do Sul, Sul, Porto Alegre, Alegre, Brazil, (e-mail: (e-mail: [email protected], [email protected]) Porto Alegre, Brazil, (e-mail: [email protected], [email protected]) Porto Alegre, Brazil, (e-mail: [email protected], [email protected]) Abstract: In aa more competitive business environment, where technology is driving major transformations, being Abstract: business environment, where is major transformations, being Abstract:ofIn In keeping a more more competitive competitive business environment, where technology technology isa driving driving major transformations, being capable up with the pace of change is crucial to remain relevant business player. Since its capable of keeping up with the pace of change is crucial to remain a relevant business player. Since its Abstract: In a more competitive business environment, where technology is driving major transformations, being Abstract:ofIn keeping aIndustry more competitive business environment, wheresome technology isachallenges driving transformations, being capable up4.0with the pace of changeat is crucial to remain relevantmajor business player. Since its introduction, (I4.0) has been aiming solving of these by encompassing multiple introduction, Industry 4.0 (I4.0) has been aiming at solving some of these challenges by encompassing multiple capable of keeping up with the pace of change is crucial to remain a relevant business player. Since its capable ofwhich keeping up4.0 with thehas pace ofaiming changeattois crucial to remain relevant business player. Since its introduction, Industry (I4.0) beenchallenge solving some ofdistinct theseachallenges by encompassing multiple concepts, leads to a considerable integrate very fields. Growing integration between concepts, which leads to a considerable challenge to integrate very distinct fields. Growing integration between introduction, Industry 4.0 (I4.0) has been aiming at solving some of these challenges by encompassing multiple introduction, Industry 4.0 (I4.0) has been aiming at solving some of these challenges by encompassing multiple concepts, which leads (IoE) to a considerable challenge tochain, integrate veryasdistinct fields. Growing integration between Internet of Everything and the industrial value as well the complexities involved in the integration Internet of Everything and value chain, as the complexities involved in concepts, leads to challenge integrate very fields. Growing integration between concepts, which leads (IoE) to aa considerable considerable challenge toCyber-Physical integrate veryas distinct fields. Systems Growing integration betweena Internet ofwhich Everything (IoE) and the the industrial industrial valueto chain, as well well asdistinct the complexities involved in the the integration integration between Cyber-Physical Systems (CPS) and Production (CPPS) require between Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS) require aa Internet of Everything (IoE) and the industrial value chain, as well as the complexities involved in the integration Internet of Everything (IoE) and the industrial value chain, as well as the complexities involved in the integration between Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS) require systematization of knowledge that allows the description of these elements, their integration, interoperability and systematization of knowledge that allows the description of these elements, their integration, interoperability and between Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS) require between Cyber-Physical Systems (CPS) and Cyber-Physical Production Systems (CPPS) require systematization of knowledge that allows the description of these elements, their integration, interoperability andaa realization of benefits expected from I4.0. Moreover, I4.0 elements have also behavioral aspects that lack aa proper realization of benefits expected from I4.0. Moreover, I4.0 elements have also behavioral aspects that lack proper systematization of knowledge that allows the description of these elements, their integration, interoperability and systematization of conceptual knowledge allows the description these have elements, integration, interoperability and realization of benefits expectedthat from I4.0. Moreover, I4.0 of elements havegaps alsotheir behavioral aspects that lack a proper representation in models. Current semantic tools in their ability to represent these representation in conceptual models. Current semantic tools have gaps in their ability to represent these realization of benefits expected from I4.0. Moreover, I4.0 elements have also behavioral aspects that lack a proper realization of benefits expected fromthat I4.0. Moreover, I4.0 elements havegaps also behavioral aspects lack a proper representation in conceptual models. Current semantic tools have inprecise their description ability tothat represent these behavioral elements. It is important this systematization also enables the of the elements behavioral elements. It that this also enables the description of elements representation in models. Current semantic tools gaps inprecise their ability represent these th th industrial representation in conceptual conceptual models. Current semantic tools have gaps their abilityofto tothe represent these behavioral elements. It is is important important that this systematization systematization alsohave enables the description of 4the the and their characteristics, including flexibility and change capability so full potential theinprecise th elements and their characteristics, including flexibility and change capability so the full potential of the 4 th industrial behavioral elements. It is important that this systematization also enables precise description of the elements behavioral elements. It is important that this systematization also enables the precise description of elements and their characteristics, including flexibility andthe change capability sodescription full potential of the 4the industrial revolution can be unleashed. To do so, addressing gaps of semantic tools, as well as proposing aa th industrial revolution can unleashed. To so, addressing the gaps of semantic description tools, as well as and their including flexibility and change capability the full the th and their characteristics, characteristics, including flexibility and change capability so the full potential potential of thepaper 4proposing industrial revolution cantobe beinclude unleashed. To do do elements so, addressing the gaps description of semanticso description tools, as of well as4 proposing a methodology behavioral in conceptual are necessary steps. This analyses methodology to behavioral in description are necessary steps. analyses revolution can unleashed. To do so, addressing the of description tools, as well as aa revolution cantowards beinclude unleashed. Tothat do elements so, addressing the gaps gaps of semantic semantic description tools, as This well paper as proposing proposing methodology tobe include behavioral elements in conceptual conceptual description are necessary steps. This paper analyses current gaps a model allows representing both structural and behavioral characteristics of I4.0 current gaps towards a model that allows representing both structural and behavioral characteristics of I4.0 methodology to include behavioral elements in conceptual description are necessary steps. This paper analyses methodology to include behavioral in conceptual description areand necessary steps. This paper analyses current gaps towards aa few model thattoelements allows representing both structural behavioral characteristics of I4.0 elements and suggests steps address these gaps. Copyright © 2019 IFAC elements and suggests steps address these © current model that both and behavioral current gaps gaps towards model thatto allows representing both structural structural andIFAC behavioral characteristics characteristics of of I4.0 I4.0 elements and towards suggests aaaa few few steps to allows addressrepresenting these gaps. gaps. Copyright Copyright © 2019 2019 IFAC Keywords: industry 4.0, conceptual model, ontology elements and suggests a few steps to address these gaps. Copyright © 2019 IFAC © 2019, IFAC (International Federation of Automatic Control) Hosting©by2019 Elsevier Ltd. All rights reserved. Keywords: industry 4.0, conceptual model, ontology elements and suggests a few steps to address these gaps. Copyright IFAC Keywords: industry 4.0, conceptual model, ontology Keywords: Keywords: industry industry 4.0, 4.0, conceptual conceptual model, model, ontology ontology or cheaper. There is also the case where aa manufacturing or cheaper. There also case or cheaper.provided There is isby alsoa the the case inwhere where a manufacturing manufacturing operation device maintenance can be operation provided by a device in maintenance can be or cheaper. There is also the case where aa manufacturing 1. INTRODUCTION or cheaper. There is also the case where manufacturing operation provided by a device in maintenance can be transferred to a different device to prevent production losses; 1. transferred to a different device to prevent production losses; 1. INTRODUCTION INTRODUCTION operation provided by a device in maintenance can be operation provided by a device in maintenance can be transferred to a different device to prevent production losses; (iii) Plant changes: whenever a plant is expanded, a new line 1. INTRODUCTION I4.0 is an initiative the German government adopted as (iii) Plant changes: whenever a plant is expanded, a new line 1.from INTRODUCTION transferred to a different device to prevent production losses; I4.0 is an initiative from the German government adopted as transferred to a different device to prevent production losses; (iii) Plant changes: whenever a plant is expanded, a new line I4.0 is an initiative from the German government adopted as of products is introduced, new technologies, efficiency Strategy 2020 Action Plan, part of High-Tech announced in of products is introduced, technologies, (iii) Plant whenever aanew plant is aaefficiency new part of High-Tech Action Plan, announced in I4.0 is an initiative from German government adopted as Plant changes: changes: whenever plantrequirements, is expanded, expanded, constraints new line line of products is introduced, new technologies, efficiency I4.0 is an initiative Strategy from the the2020 German government adopted as part of(Kagermann, High-Tech Strategy 2020 Action Plan, announced in (iii) improvement, compliance with new 2011 Wahlster, and Helbig 2013b). The reason improvement, compliance with new requirements, constraints of products is introduced, new technologies, efficiency 2011 (Kagermann, Wahlster, and Helbig 2013b). The reason part of High-Tech Strategy 2020 Action Plan, announced in of products is introduced, new technologies, efficiency improvement, compliance with new requirements, constraints part of(Kagermann, High-Tech Strategy 2020 Action Plan, announced in and 2011 Wahlster, and Helbig 2013b). The reason regulations are needed, the existing CPPS needs to adapt for using this name is that the previous three industrial and regulations are needed, the existing CPPS needs to with requirements, constraints improvement, compliance for using this name is the previous three industrial 2011 (Kagermann, Wahlster, and Helbig 2013b). reason improvement, compliance with new requirements, constraints regulations are needed, the new existing CPPS needs to adapt adapt 2011 (Kagermann, Wahlster, and Helbig 2013b). The reason and for using this name is a that that the previous threeThe industrial to integrate the new capabilities, while making sure they revolutions happened as result of mechanization, electricity to integrate the new capabilities, while making sure they needs to adapt and regulations are needed, the existing CPPS revolutions happened as a result of mechanization, electricity for using this name is that the previous three industrial and regulations are needed, the existing CPPS needs to adapt to integrate the new capabilities, while making sure they for using this name the three industrial revolutions happened asis a that result ofInprevious mechanization, electricity remain compatible with existing ones. All aforementioned and information technology (IT). 2013, the “Industrie 4.0 remain compatible with existing ones. All aforementioned to integrate the new capabilities, while making sure they and information technology (IT). In 2013, the “Industrie 4.0 revolutions happened as a result of mechanization, electricity to integrate the new capabilities, while making sure they remain compatible with existing ones. All aforementioned situations are examples of situations that can be addressed revolutions happened as a result ofInmechanization, electricity and information technology (IT). 2013, the “Industrie 4.0 Working Group” published the first recommendations for the situations are examples of situations that can be addressed remain compatible with existing ones. All aforementioned Working Group” published the first recommendations for the and information technology (IT). In 2013, the “Industrie 4.0 remain compatible with existing ones. All aforementioned situations are examples of situations that can be addressed through the use of I4.0 elements. and information technology (IT). In 2013, the “Industrie 4.0 Working Group”ofpublished the first recommendations for the situations implementation I4.0, highlighting Internet of Things (IoT), through use of of implementation of I4.0, Internet of Things (IoT), Working Group” the the situationsthe are examples of situations situations that that can can be be addressed addressed through theare useexamples of I4.0 I4.0 elements. elements. Working Group” published the first firstasrecommendations recommendations for the implementation ofpublished I4.0, highlighting highlighting Internet ofcomponents Thingsfor (IoT), CPS and smart factories, or CPPS, the main of through the use of I4.0 elements. Different attempts have been made to define I4.0 elements, but CPS and smart factories, or CPPS, as the main components of implementation of I4.0, highlighting Internet of Things (IoT), through the use of I4.0 elements. Different attempts have been made to define I4.0 elements, but implementation of I4.0, highlighting Internet of Things (IoT), CPS and smart factories, or CPPS, as the main components of (Kagermann, Wahlster, and Helbig 2013b). I4.0 The Different attempts have been made toaround define I4.0 elements, but there is no complete consensus their definitions. I4.0 (Kagermann, Wahlster, and Helbig 2013b). The CPS and smart factories, or CPPS, as the main components of there is no complete consensus around their definitions. Different attempts have been made to define I4.0 elements, but CPS and smart factories, or CPPS, as the main components of I4.0 (Kagermann, Wahlster, and Helbig 2013b). The introduction of such concepts is enabling the fourth industrial Different attempts have been made to define I4.0 elements, but there is no complete consensus around their definitions. However, design principles, conceptual descriptions and even introduction of concepts is the fourth industrial I4.0 Wahlster, and Helbig 2013b). The However, design principles, conceptual descriptions and even there is no complete consensus around their definitions. I4.0 (Kagermann, (Kagermann, Wahlster, and Helbig 2013b). The introduction of such such concepts is enabling enabling theand fourth industrial revolution. This trend is intended to address overcome the there is no complete consensus around their definitions. However, design principles, conceptual descriptions and even architecture models have been presented within I4.0 idea revolution. This trend is intended to overcome the introduction of concepts is the fourth industrial architecture models have been presented within I4.0 idea introductionfaced of such such concepts is enabling enabling theand fourth industrial revolution. This trend ismanufacturing intended to address address and overcome the However, principles, conceptual descriptions and even challenges in the field, especially shorter However, design principles, conceptual descriptions and Hess even architecture models have been presented within and I4.0 idea (Hermann,design Pentek, and Otto 2016; Vogel-Heuser challenges faced in the manufacturing field, especially shorter revolution. This trend is intended to address and overcome the Pentek, and Otto 2016; Vogel-Heuser and Hess revolution.lifecycles, This trend intendedcustomized to address overcome the (Hermann, challenges faced in theishighly manufacturing field, and especially shorter architecture models have been presented within I4.0 idea products, new product architecture models have been presented within I4.0 idea (Hermann, Pentek, and Otto 2016; Vogel-Heuser and Hess product lifecycles, highly customized products, new 2016; Hankel and Rexroth 2015; Bagheri et al. 2015; Weyrich challenges faced in manufacturing field, especially shorter 2016; Hankel and Rexroth 2015; Bagheri et al. 2015; Weyrich (Hermann, Pentek, and Otto 2016; Vogel-Heuser and Hess challengeslifecycles, faced in the thetohighly manufacturing field, especially shorter product customized products, new requirements related sustainability, regulatory, safety and (Hermann, Pentek, and Otto 2016; Vogel-Heuser and Hess 2016; Hankel and Rexroth 2015; Bagheri et al. 2015; Weyrich and Ebert 2016). Researches on most design principles and requirements related to sustainability, regulatory, safety and product lifecycles, highly customized products, new and Ebert 2016). Researches on most principles and product lifecycles, customized products, Hankel and 2015; et al. Weyrich requirements related tohighly sustainability, regulatory, safety new and 2016; technology, and stiff global competition. 2016; Hankel and Rexroth Rexroth 2015; Bagheri et promising al. 2015; 2015; Weyrich and Ebert 2016). Researches onBagheri most design design principles and I4.0 related technologies already delivered results, technology, and stiff global competition. requirements related to sustainability, regulatory, safety and I4.0 related technologies already delivered promising results, Researches on most design principles and Ebert 2016). requirementsand related to sustainability, technology, stiff global competition.regulatory, safety and and and Ebert 2016). Researches on most design principles and I4.0 related technologies already delivered promising results, but full benefits will only be achieved by “combining all These elements to deal with common situations technology, and stiff global but full benefits will only be achieved by “combining all promising results, I4.0 related technologies already delivered technology, and are stiffessential global competition. competition. These elements are essential to deal with common situations I4.0 related technologies already delivered promising results, but full benefits will only be achieved by “combining all These elements are essential to customization, deal with common situations aspects synergistically and considering the constraints from such as: (i) Mass product when highly aspects synergistically and considering the constraints from but full benefits will only be achieved by “combining all such as: (i) Mass product customization, when highly These elements are essential to deal with common situations but full benefits will only be achieved by “combining all aspects synergistically and considering the constraints from automation especially automated production systems as realThese as: elements are essential to customization, deal flexible with common situations such (i)product Mass product when highly customized orders demand adaptation of aa aspects automation especially automated production systems as realsynergistically and considering the constraints from customized product orders demand flexible adaptation of such as: (i) Mass product customization, when highly aspects synergistically and considering the constraints from automation especially automated production systems as realtime, dependable, safety standard compliant systems, such as: (i)product Mass product customization, when highly customized orders demand flexiblecan adaptation of a time, dependable, safety standard compliant systems, manufacturing plant. This kind of product even require automation especially automated production systems as manufacturing plant. This kind of can even customized product demand flexible adaptation of automation especially automated production systemssystems, as realrealdependable, safety standard compliant providing concepts for diagnosis and fault handling” (Vogelcustomized product orders demand flexible adaptation of aa time, manufacturing plant.orders Thisthat kind ofnotproduct product can even require require manufacturing operations do exist in a specific plant. providing concepts for diagnosis and fault handling” (Vogeltime, dependable, safety standard compliant systems, operations that do not exist in a specific plant. manufacturing plant. This kind of product can even require time, dependable, standard compliant systems, providing concepts forsafety diagnosis and fault handling” (Vogelplant. This kind of product can even require manufacturing operations that do not exist in a specific plant. Heuser and Hess 2016). A conceptual model that describes all This situation can potentially be solved by either reconfiguring Heuser and Hess 2016). A model that describes all providing concepts for diagnosis and handling” (VogelThis situation can potentially be solved by either reconfiguring manufacturing operations that do not exist in aa specific plant. providing concepts for characteristics diagnosis and fault fault handling” (VogelHeuser and Hess 2016). A conceptual conceptual model that describes all manufacturing operations that do not exist in specific plant. This situation can potentially be solved by either reconfiguring concepts and desirable is still a gap (Hermann, the plant, adding new devices that carry the specific capability concepts and desirable characteristics is still a gap (Hermann, Heuser and Hess 2016). A conceptual model that describes all the plant, adding new devices that carry the specific capability This situation can potentially solved by either reconfiguring Heuser and Hess 2016).2016). A conceptual model all concepts and desirable characteristics is still athat gapdescribes (Hermann, This situation can potentially be solved by either reconfiguring the plant, adding new devicesbe that carry the specific capability Pentek, and Otto Existing works related to required or rely on a different plant that is able to provide that Pentek, and Otto 2016). Existing works related to concepts and desirable characteristics is still aa gap (Hermann, required or rely on a different plant that is able to provide that the plant, adding new devices that carry the specific capability concepts and desirable characteristics is still gap (Hermann, Pentek, and Otto 2016). Existing works related to the plant,oradding new devicesneeds, that the specific capability required relyMaintenance on a different plantcarry that is able to provide that manufacturing field ontologies and conceptual models usually breakdowns and capability; (ii) avoiding manufacturing field ontologies and conceptual models usually Pentek, and Otto 2016). Existing works related to capability; (ii) Maintenance needs, avoiding breakdowns and required or rely on a different plant that is able to provide that Pentek, and Otto 2016). Existing works related to manufacturing field ontologies and conceptual models usually required or (ii) rely on can a different plant that is ablebreakdowns to provide that capability; Maintenance needs, avoiding anda manufacturing focus on structural elements (devices, machines, software, production losses be achieved by means of adapting focus on structural elements (devices, machines, software, field ontologies and conceptual models usually production losses can be achieved by means of adapting a capability; (ii) Maintenance needs, avoiding breakdowns and manufacturing field ontologies and conceptual models usually focus on structural elements (devices, machines, software, infrastructure and other static components), rather than capability; (ii) Maintenance needs, avoiding breakdowns anda focus production losses can be down achieved by to means of adapting device usage e.g. slowing its use make its forecasted and static components), rather than elements (devices, machines, software, device usage e.g. slowing its make its forecasted production can be achieved by means aa infrastructure focus on on structural structural elements (devices, machines, software, infrastructure and other other static components), rather than production losses canwhen be down achieved by to means of adapting device usagelosses e.g. slowing down its use use to makeof its adapting forecasted failure date in a time a maintenance operation is easier, infrastructure and other static components), rather than failure date in a time when a maintenance operation is easier, device usage e.g. slowing down its use to make its forecasted infrastructure and other static components), rather than device date usageine.g. slowing its use to operation make its forecasted failure a time whendown a maintenance is easier, failure in aa maintenance operation is 2405-8963 © 2019, IFACwhen (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. failure date date in aa time time when maintenance operation is easier, easier,

Copyright 2019 IFAC 879 Peer review© of International Federation of Automatic Copyright ©under 2019 responsibility IFAC 879Control. Copyright © 2019 IFAC 879 10.1016/j.ifacol.2019.11.238 Copyright 879 Copyright © © 2019 2019 IFAC IFAC 879

2019 IFAC MIM 864 Berlin, Germany, August 28-30, 2019

Thiago Regal et al. / IFAC PapersOnLine 52-13 (2019) 863–868

behavioral aspects, such as flexibility and change capabilities, which are critical in I4.0 elements.

Systems change capabilities, considered in the sense of changing, adapting and evolving in a fast, efficient and autonomous manner, despite being part of most design principles efforts, are a significant gap in formal modelling for production systems (Gronau et al. 2016). Modelling systems change capability would allow virtual simulations to evaluate alternative designs or even multiple market scenarios on which corporate strategy and investment decisions could be made. Providing a way to model systems which are “changeable by design” would potentially lead CPPS to be more compliant with flexible, adaptive behavior described in (Vogel-Heuser and Hess 2016).

This paper intends to outline the gaps around I4.0 conceptual modelling, highlighting the need to model behavioral aspects in I4.0 (in addition to structural elements) and the required advancements in semantic modelling tools to achieve that purpose. It is organized in the following topics: a state-of-theart analysis, considerations on the gaps for structural and behavioral modelling and semantic tools. At the end, a conclusion and future works section.

2.

STATE-OF-THE-ART ANALYSIS

2.2 Conceptual models and ontologies in manufacturing

2.1 I4.0 definitions

Multiple proposals around concepts related to manufacturing fields have been made in the past decades and, more recently, considered I4.0 elements and ideas, with a considerable advancement in the field. When examining available works, most of them (reference architectures, conceptual models and ontologies) can be organized as including or not I4.0 elements, how they describe or use semantic formalisms and whether they describe behaviors, such as change capability and flexibility, or not.

Different attempts have been made to define I4.0, related to the integration of complex machines and devices, in a networked environment, meant to answer to current requirement on the value chain, allowing better control over it, which (Kagermann, Wahlster, and Helbig 2013a) defined as “a new level of value chain organization and management across the lifecycle of products”. A slightly different definition is proposed by (Hermann, Pentek, and Otto 2016) stating that I4.0 refers to technologies and concepts of value chain organization, in which CPS monitor physical processes, creating a virtual copy of the real world and making decentralized decisions, while over IoT, CPS communicates and cooperates with each other and with humans in real time. In Internet of Services (IoS), internal and cross-organizational services are offered and used by actors in the value chain.

Some works have a more traditional approach, describing manufacturing elements and descriptions involved in manufacturing such as devices, machines, sensors and others, without necessarily describing I4.0 scenarios (Garetti and Fumagalli 2012; Ameri, Urbanovsky, and McArthur 2012; Lemaignan et al. 2006; Garetti et al. 2013; H. K. Lin and Harding 2007). Description of concepts, attributes and relations in conceptual models is not exclusive of manufacturing elements. Some works describe modelling of manufacturing processes and products (Brunoe et al. 2018), while others focus on characteristics such as interoperability, communication and integration (Hankel and Rexroth 2015; Ray 2016; Ivanov et al. 2016). Even specific domains modelling is proposed (e.g. supply chain) (Postránecký and Svítek 2017; Yang and Yan 2011) or applications (e.g. integration between spare parts supply chain and intelligent maintenance systems) (Da Silva et al. 2014).

The paradigm of I4.0 is essentially outlined by (T. Bauernhansl, B. Diegner, J. Diemer 2014; Kagermann, Lukas, and Wahlster 2011; Stock and Seliger 2016) as (i) horizontal integration across all value creation network, (ii) end-to-end engineering across the entire product lifecycle and (iii) vertical integration and networked manufacturing systems. Horizontal integration across the value creation network refers to crossconnection and integration to all actors playing in the value creation network involved in specific product lifecycles. Endto-end engineering refers to the intelligent cross-linking and digitalization throughout all phases of a product lifecycle, from raw material acquisition to manufacturing systems, product use and product end-of-life. Networked manufacturing systems and vertical integration describe intelligent crosslinking and digitalization within different aggregation and hierarchical levels within manufacturing modules that create value in manufacturing cells, lines and factories, integrated with associated value chain activities, such as sales, engineering, maintenance and marketing.

Structural description of manufacturing fields with the presence of I4.0 elements in the model is also described by emphasizing common elements in I4.0, such as CPS and CPPS characteristics, properties e relationships, the smart* concepts (smart-factories, smart-cities) and their interrelation and interconnection throughout the whole industrial value chain (Zheng et al. 2018; Varga et al. 2017; Thi and Helfert 2017; Takahashi, Ogata, and Nonaka 2017).

In spite of the fact there is no complete consensus around definitions of I4.0 elements, design principles, conceptual descriptions and even architecture models have been presented within I4.0 idea (Hermann, Pentek, and Otto 2016; VogelHeuser and Hess 2016; Hankel and Rexroth 2015; Bagheri et al. 2015; Weyrich and Ebert 2016). Most of them agree on some design principles (Vogel-Heuser and Hess 2016) that will be detailed in the next sections.

Just a few describe the use of semantic formalisms (Järvenpää et al. 2018; Ameri, Urbanovsky, and McArthur 2012), while a few describe behaviors and, when they do it, it is focused on communication and interoperability (Järvenpää et al. 2018; Brad, Murar, and Brad 2018; Lemaignan et al. 2006). Modelling I4.0 systems behaviors, using proper semantic formalisms, specially flexibility and change capability is clearly a gap (Vogel-Heuser and Hess 2016). Table 1 lists the main works in the area and their characteristics. 880

2019 IFAC MIM Berlin, Germany, August 28-30, 2019

Thiago Regal et al. / IFAC PapersOnLine 52-13 (2019) 863–868

Internet of Things Architecture (IoT-A) (Ray 2016)

Provide detailing of IT aspects in IoT, especially from functional and informational perspectives. Maintained by big Industrial players, this architecture Internet is focused on Reference manufacturing aspects. It Architecture proposes five main (IIRA) (S.-W. functional domains: Lin and Miller control, operation, 2016) information, application and business. Smartness level (Postránecký and modelling in multi agent Svítek 2017) systems in smart cities. Reference architecture for smart factories, largely based on IEC Reference standards, it has gaps in Architecture the identification of Model Industrie elements and 4.0 (RAMI 4.0) interoperability and (Hankel and communication Rexroth 2015) semantics that, potentially, could be addressed through an ontology. P-PSO (Garetti Use in information and Fumagalli exchange, design and 2012) control activities. MSDL (Ameri, Proposes a Urbanovsky, and manufacturing services McArthur 2012) representation. Upper ontology for MASON manufacturing, other (Lemaignan et al. ontologies can be 2006) derived from it. Model that demonstrates the use of a layered and (Zdravković et al. extensible to model 2011) manufacturing systems elements. Layered architecture, (Yang and Yan with an upper ontology 2011) and a domain ontology.

Table 1. Main related works Related Work

(Brad, Murar, and Brad 2018)

MaRCO (Järvenpää et al. 2018)

(Brunoe et al. 2018)

(Zheng et al. 2018)

Arrowhead Framework (Varga et al. 2017)

IASDO (Thi and Helfert 2017)

Main Characteristics Provides a method for the design of manufacturing resources connection focusing on enabling changeability and reconfigurability Describes a systematic methodology to describe a manufacturing system capability through an ontology based on OWL. It analyses how integrated modelling of products and processes can be applied in the design, management and operation of changeable manufacturing systems Covers many topics, including smart design, smart machining, smart monitoring, smart control, smart scheduling e industrial implementation. Presents a proposal for a structure of many elements of I4.0. Proposes collaborative automation through embedded devices in an open network. It is a big project of EU to enable the use of best practices in cooperative automation. Modelling of information products to systematically represent changes involved in manufacturing or creation of this kind of product.

Semantic formalism

No

OWL

No

No

No

No

Standard for an Architectural Framework for the Internet of Things (IoT) (Takahashi, Ogata, and Nonaka 2017)

Focus on aspects such as protection, safety and No privacy questions.

(Ivanov et al. 2016)

Focus on short term scheduling in supply chain in the context of smart factories and I4.0.

865

No

No

No

No

UML

OWL/SWRL

OWL

No

No

2.3 I4.0 vocabulary and design principles Generally accepted understanding and a vocabulary on the term Industry 4.0 and its multiple components and characteristics are still a challenge (Vogel-Heuser and Hess 2016; Hermann, Pentek, and Otto 2016). However, design principles, conceptual descriptions and even architecture models have been presented within Industry 4.0 idea (Hermann, Pentek, and Otto 2016; Vogel-Heuser and Hess 2016; Hankel and Rexroth 2015; Bagheri et al. 2015; Weyrich and Ebert 2016). Most of them agree on the following principles (Vogel-Heuser and Hess 2016):

No

881

2019 IFAC MIM 866 Berlin, Germany, August 28-30, 2019

Thiago Regal et al. / IFAC PapersOnLine 52-13 (2019) 863–868



Service orientation;



Intelligent self-organization;



Humans, CPS (interoperability);



Flexible adaptation to changing requirements;



Big data algorithms and technologies, enhancing decision making capabilities, for example;



Optimization of the manufacturing process based on big data algorithms and real-time technologies to increase Overall Equipment Effectiveness (OEE);



Data integration across disciplines and life cycle based on standard data models and model driven engineering;



Secure communication and ability to networking with other companies and CPPS;



Data securely stored in a cloud or intranet.

and

CPPS

standard language (McGuinness and Harmelen 2004), based on XML and with a structure that allows machine processing of concepts, relations and other elements. Different degrees of formalisms and support to reasoning differentiate many of the available languages today. While languages such as XML(S), XOL and UML do not support reasoning, RDF(S), OWL Full, DAML+OIL and DAML do support it, but not in finite time, adding a constraint to its use. Markup languages, derived from UML, such as SysML and AutomationML have found great acceptance in systems modelling and automation modelling, but lack formalism.

communication

Most of the works proposing conceptual models or reference architectures to I4.0 elements available in the literature either describe the proposal without providing details of any semantic support or use some language to describe it, mostly focused on structural aspects. No suggestion of semantic support to describe behavior was found, but literature also suggests that combining languages to address gaps is also a foreseeable approach (Gronau et al. 2016).

3.

While researches on most design principles and I4.0 related technologies already delivered promising results, description of its concepts and desirable characteristics are a gap (Hermann, Pentek, and Otto 2016) which prevents leveraging its full benefits in industrial value chain (Vogel-Heuser and Hess 2016). Some of these principles describe a flexible, adaptable behavior that is key to deliver the benefits expected from CPPS.

GAPS FOR A STRUCTURAL AND BEHAVIOURAL MODEL OF I4.0 ELEMENTS

3.1 Addressing semantic formalism gaps In order to properly describe I4.0 elements in their entirety, including both structural and behavioral elements, an important starting point is to define which elements should be specifically described, especially in the behavioral aspect. From all characteristics related to I4.0 systems, flexibility is one of the most critical and necessary characteristics in today’s manufacturing field (Jain et al. 2013). It is a broad concept which, in manufacturing field, can be defined as the ability to adjust to cope with environmental changes with small impact in time, effort, cost and performance. Manufacturing flexibility is a multidimensional and complex construct, and literature has been ambiguous about its definition and the aspects that constitute it, leading to some attempts to systematize this knowledge (Pérez, Bedia, and López Fernández 2016). Therefore, defining flexibility and proposing a way to model it is an important step towards more comprehensive I4.0 models.

2.4 Semantic modelling languages Conceptual modelling with the use of semantic formalisms, reasoning mechanisms and behavioral representation of I4.0 elements can enable industry to deal with shorter lifecycles, time-to-market, mass customization and competition for costs and quality in global scale (Ivanov et al. 2016; T. Bauernhansl, B. Diegner, J. Diemer 2014; Kagermann, Lukas, and Wahlster 2011; Stock and Seliger 2016; Hermann, Pentek, and Otto 2016; Vogel-Heuser and Hess 2016). Through the years, many languages were developed to represent ontologies in a formal way (Corcho and GómezPérez 2000). Among those considered as traditional languages, i.e. the first to be developed, are Ortolingua, (Farquhar, Fikes, and Rice 1997), maybe the most representative, OKBC (Chaudhri et al. 1997), OCML (Motta 1999), FLogic (Kifer, Lausen, and Wu 1995), LOOM (MacGregor 1991). Many works also used UML (Garetti and Fumagalli 2012; Zhao and Zhu 2010), or even C++ (Fadel, Fox, and Gruninger 1994) as a tool to represent their semantics.

3.2 Proposing a set of structural and behavioral aspects to model A second gap to be addressed is to propose a set of structural and behavioral aspects to be included in the model. Interoperability, integration, communication, establishment of a common vocabulary, all have already been addressed by literature. Adding changeability by design capabilities, flexibility and other behavioral characteristics will enable industry to take full advantage of I4.0 elements (Vogel-Heuser and Hess 2016).

However, with the need of cooperation among agents and the network exchange of ontologies, a new set of languages was developed, based on standards that were friendly to the internet, such as XML and RDF. W3C (World Wide Web Consortium) adopted OWL (Web Ontology Language) as a

3.3 Proposing a methodology to elicit behavioral and structural characteristics and to build the model

882

2019 IFAC MIM Berlin, Germany, August 28-30, 2019

Thiago Regal et al. / IFAC PapersOnLine 52-13 (2019) 863–868

A third gap to be addressed is to propose a method to elicit characteristics from different I4.0 elements and systems. As manufacturing field, systems and technologies are getting more complex and heterogeneous, non-standardized systems are very often used. Being able to translate characteristics and needs from the real world to a model can be a complex task, only achievable by a methodology to make this area representable in a conceptual model.

Systems, 328–35. Chaudhri, Vinay K, Adam Farquhar, Richard Fikes, Peter D Karp, and James Rice. 1997. “The Generic Frame Protocol 2.0.” Artificial Intelligence Center, SRI International. Knowledge Systems Laboratory, Stanford University. Corcho, Oscar, and Asunción Gómez-Pérez. 2000. “A Roadmap to Ontology Specification Languages.” In International Conference on Knowledge Engineering and Knowledge Management, 80–96. Fadel, Fadi George, Mark S Fox, and Michael Gruninger. 1994. “A Generic Enterprise Resource Ontology.” In Enabling Technologies: Infrastructure for Collaborative Enterprises, 1994. Proceedings., Third Workshop On, 117–28. Farquhar, Adam, Richard Fikes, and James Rice. 1997. “The Ontolingua Server: A Tool for Collaborative Ontology Construction.” International Journal of Human Computer Studies. doi:10.1006/ijhc.1996.0121. Garetti, M., and L. Fumagalli. 2012. “P-PSO Ontology for Manufacturing Systems.” In IFAC Proceedings Volumes (IFAC-PapersOnline). doi:10.3182/201205233-RO-2023.00222. Garetti, M., L. Fumagalli, A. Lobov, and J. L. Martinez Lastra. 2013. “Open Automation of Manufacturing Systems through Integration of Ontology and Web Services.” In IFAC Proceedings Volumes (IFACPapersOnline). doi:10.3182/20130619-3-RU3018.00169. Gronau, Norbert, Birgit Vogel-Heuser, Edzard Weber, André Ullrich, and Daniel Schütz. 2016. “Modellability of System Characteristics - Using Formal Mark-up Languages for Change Capability by Design.” Procedia CIRP 52. Elsevier B.V.: 118–23. doi:10.1016/j.procir.2016.07.074. Hankel, Martin, and Bosch Rexroth. 2015. “The Reference Architectural Model Industrie 4.0 (Rami 4.0).” ZVEI. Hermann, Mario, Tobias Pentek, and Boris Otto. 2016. “Design Principles for Industrie 4.0 Scenarios.” In System Sciences (HICSS), 2016 49th Hawaii International Conference On, 2016–March:3928–37. doi:10.1109/HICSS.2016.488. Ivanov, Dmitry, Alexandre Dolgui, Boris Sokolov, Frank Werner, and Marina Ivanova. 2016. “A Dynamic Model and an Algorithm for Short-Term Supply Chain Scheduling in the Smart Factory Industry 4.0.” International Journal of Production Research. doi:10.1080/00207543.2014.999958. Jain, Ajai, P K Jain, Felix T S Chan, and Shailendra Singh. 2013. “A Review on Manufacturing Flexibility” 51 (19): 5946–70. Järvenpää, Eeva, Niko Siltala, Otto Hylli, and Minna Lanz. 2018. “The Development of an Ontology for Describing the Capabilities of Manufacturing Resources.” Journal of Intelligent Manufacturing. Springer, 1–20. Kagermann, Henning, Wolf-Dieter Lukas, and Wolfgang Wahlster. 2011. “Industrie 4.0: Mit Dem Internet Der

3.4 Use of reasoning and simulation tools A fourth gap to be addressed is related to the use of reasoning tools to model and validate behavior in conceptual models, ensuring consistence when applying changes. The purpose here is twofold: on one hand, the use of reasoners can help to keep the integrity of the model by preventing the introduction of unwanted changes. On the other hand, it can also support inferences to enable adaptation of the model by identifying possible elements that can perform similar tasks, for example. Also, simulations can provide different insights from changing configurations in manufacturing plans and the whole manufacturing value chain. 4.

CONCLUSIONS AND FUTURE WORKS

The ability to model I4.0 elements, describing both structural and behavioral elements can enable industry to take full advantage of the concepts involved in the area. This paper presented the current gaps preventing this to happen: (i) semantic formalisms do not have full ability to describe behavior; (ii) a method to elicit which characteristics and properly define an approach to model I4.0 elements, making use of the above-mentioned semantic tools, is also a necessary contribution to the field; and, finally, (iii) it is necessary to address the gaps both in semantic languages and methodological approaches to enable the modelling of I4.0 elements and its behavior, in order to unleash full benefits from I4.0. 5.

867

REFERENCES

Ameri, Farhad, Colin Urbanovsky, and Christian McArthur. 2012. “A Systematic Approach to Developing Ontologies for Manufacturing Service Modeling.” In CEUR Workshop Proceedings. Bagheri, Behrad, Shanhu Yang, Hung-An An Kao, and Jay Lee. 2015. Cyber-Physical Systems Architecture for Self-Aware Machines in Industry 4.0 Environment. IFAC-PapersOnLine. Elsevier. https://www.sciencedirect.com/science/article/pii/S240 5896315005571?via%3Dihub. Brad, Stelian, Mircea Murar, and Emilia Brad. 2018. “Design of Smart Connected Manufacturing Resources to Enable Changeability, Reconfigurability and TotalCost-of-Ownership Models in the Factory-of-theFuture.” International Journal of Production Research. doi:10.1080/00207543.2017.1400705. Brunoe, Thomas Ditlev, Daniel G H Sorensen, Mads Bejlegaard, Ann-Louise Andersen, and Kjeld Nielsen. 2018. “Product-Process Modelling as an Enabler of Manufacturing Changeability.” In IFIP International Conference on Advances in Production Management 883

2019 IFAC MIM 868 Berlin, Germany, August 28-30, 2019

Thiago Regal et al. / IFAC PapersOnLine 52-13 (2019) 863–868

Silva, Thiago Regal Da, Philipp Saalmann, Ann Kristin Cordes, Anderson Giacomolli, Carlos Eduardo Pereira, and Bernd Hellingrath. 2014. “Integration Architecture of Intelligent Maintenance Systems and Spare Parts Supply Chain Planning.” In Procedia CIRP, 25:192– 98. doi:10.1016/j.procir.2014.10.029. Stock, T., and G. Seliger. 2016. “Opportunities of Sustainable Manufacturing in Industry 4.0.” Procedia CIRP 40 (Icc): 536–41. doi:10.1016/j.procir.2016.01.129. T. Bauernhansl, B. Diegner, J. Diemer, et al. 2014. “Industrie 4.0: Whitepaper FuE-Themen.” Plattform Industrie 4.0. doi:10.1007/s11576-014-0424-4. Takahashi, Kiyotaka, Yuji Ogata, and Youichi Nonaka. 2017. “A Proposal of Unified Reference Model for Smart Manufacturing.” In Automation Science and Engineering (CASE), 2017 13th IEEE Conference On, 964–69. Thi, Thanh Thoa Pham, and Markus Helfert. 2017. “Modelling Information Manufacturing Systems.” ArXiv Preprint ArXiv:1704.06226 1 (1). Varga, Pal, Fredrik Blomstedt, Luis Lino Ferreira, Jens Eliasson, Mats Johansson, Jerker Delsing, and Iker Martínez de Soria. 2017. “Making System of Systems Interoperable – The Core Components of the Arrowhead Framework.” Journal of Network and Computer Applications. doi:10.1016/j.jnca.2016.08.028. Vogel-Heuser, Birgit, and Dieter Hess. 2016. “Guest Editorial Industry 4.0-Prerequisites and Visions.” IEEE Transactions on Automation Science and Engineering. doi:10.1109/TASE.2016.2523639. Weyrich, Michael, and Christof Ebert. 2016. “Reference Architectures for the Internet of Things.” IEEE Software 33 (1): 112–16. doi:10.1109/MS.2016.20. Yang, Jian, and Jianyuan Yan. 2011. “Towards a Hierarchical Supply Chain Ontology.” In 8th International Conference on Service Systems and Service Management - Proceedings of ICSSSM’11. doi:10.1109/ICSSSM.2011.5959440. Zdravković, Milan, Hervé Panetto, Miroslav Trajanović, and Alexis Aubry. 2011. “An Approach for Formalising the Supply Chain Operations.” Enterprise Information Systems. doi:10.1080/17517575.2011.593104. Zhao, Xiuxu, and Yuming Zhu. 2010. “Research of FMEA Knowledge Sharing Method Based on Ontology and the Application in Manufacturing Process.” In 2010 2nd International Workshop on Database Technology and Applications, DBTA2010 - Proceedings. doi:10.1109/DBTA.2010.5658936. Zheng, Pai, Honghui wang, Zhiqian Sang, Ray Y. Zhong, Yongkui Liu, Chao Liu, Khamdi Mubarok, Shiqiang Yu, and Xun Xu. 2018. Smart Manufacturing Systems for Industry 4.0: Conceptual Framework, Scenarios, and Future Perspectives. Frontiers of Mechanical Engineering. Vol. 13. Higher Education Press. doi:10.1007/s11465-018-0499-5.

Dinge Auf Dem Weg Zur 4. Industriellen Revolution.” VDI Nachrichten, no. 13: 3–4. http://www.vdinachrichten.com/Technik-Gesellschaft/Industrie-40Mit-Internet-Dinge-Weg-4-industriellen-Revolution. Kagermann, Henning, Wolfgang (German Research Center for Artificial Intelligence) Wahlster, and Johannes (Deutsche Post AG) Helbig. 2013a. “Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0.” Final Report of the Industrie 4.0 WG. doi:10.13140/RG.2.1.1205.8966. Kagermann, Henning, Wolfgang Wahlster, and Johannes Helbig. 2013b. “Securing the Future of German Manufacturing Industry: Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0.” Final Report of the Industrie 4.0 Working Group. doi:10.13140/RG.2.1.1205.8966. Kifer, Michael, Georg Lausen, and James Wu. 1995. “Logical Foundations of Object-Oriented and FrameBased Languages.” Journal of the ACM. doi:10.1145/210332.210335. Lemaignan, S??verin, Ali Siadat, Jean Yves Dantan, and Anatoli Semenenko. 2006. “MASON: A Proposal for an Ontology of Manufacturing Domain.” In Proceedings - DIS 2006: IEEE Workshop on Distributed Intelligent Systems - Collective Intelligence and Its Applications. doi:10.1109/DIS.2006.48. Lin, H. K., and J. A. Harding. 2007. “A Manufacturing System Engineering Ontology Model on the Semantic Web for Inter-Enterprise Collaboration.” Computers in Industry. doi:10.1016/j.compind.2006.09.015. Lin, Shi-Wan, and Bradford Miller. 2016. “Industrial Internet: Towards Interoperability and Composability.” MacGregor, Robert M. 1991. “Inside the LOOM Description Classifier.” ACM SIGART Bulletin. doi:10.1145/122296.122309. McGuinness, Deborah L, and Frank van Harmelen. 2004. “OWL Web Ontology Language - Reference.” W3C Recommendation [Online], Available at: Http://Www.W3.Org/TR/2004/REC-Owl. doi:16/j.jss.2010.10.025. Motta, Enrico. 1999. Reusable Components for Knowledge Modelling: Case Studies in Parametric Design Problem Solving. Vol. 53. IOS press. Pérez, Marta Pérez, Ana María Serrano Bedia, and María Concepción López Fernández. 2016. “A Review of Manufacturing Flexibility: Systematising the Concept.” International Journal of Production Research 54 (10): 3133–48. doi:10.1080/00207543.2016.1138151. Postránecký, Michal, and Miroslav Svítek. 2017. “Conceptual Model of Complex Multi-Agent System Smart City 4.0.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). doi:10.1007/978-3-319-64635-0_16. Ray, P. P. 2016. “A Survey on Internet of Things Architectures.” Journal of King Saud University Computer and Information Sciences. doi:10.1016/j.jksuci.2016.10.003. 884