Process planning is the activity of determining the manufacturing operations needed to produce a product. The knowledge work of process planning has been thoroughly investigated. Several ideas to automate process planning have been proposed but their success in practice has not yet been realized. Little attention has been given to design as an inevitable element in process planning and the role of human expertise in process design. From the premise that competent planners are a primary source of productivity this paper discusses process design, the role of human expertise and how CAPP systems could support human decision making.

Learning factories present a promising environment for education, training and research, especially in manufacturing related areas which are a main driver for wealth creation in any nation. While numerous learning factories have been built in industry and academia in the last decades, a comprehensive scientific overview of the topic is still missing. This paper intends to close this gap by establishing the state of the art of learning factories. The motivations, historic background, and the didactic foundations of learning factories are outlined. Definitions of the term learning factory and the corresponding morphological model are provided. An overview of existing learning factory approaches in industry and academia is provided, showing the broad range of different applications and varying contents. The state of the art of learning factories curricula design and their use to enhance learning and research as well as potentials and limitations are presented. Conclusions and an outlook on further research priorities are offered. (C) 2017 Published by Elsevier Ltd on behalf of CIRP.

While design of production systems based on digital models brings benefits, the communication of models comes with challenges since models typically reside in a heterogeneous IT environment using different syntax and semantics. Coping with heterogeneity requires a smart integration strategy. One main paradigm to integrate data and IT systems is to deploy information standards. In particular, ISO 10303 STEP has been endorsed as a suitable standard to exchange a wide variety of product manufacturing data. One the other hand, service-oriented tool integration solutions are progressively adopted for the integration of data and IT-tools, especially with the emergence of Open Services for Lifecycle Collaboration whose focus is on the linking of data from heterogeneous software tools. In practice, there should be a combination of these approaches to facilitate the integration process. Hence, the aim of this paper is to investigate the applications of the approaches and the principles behind them and try to find criteria for where to use which approach. In addition, we explore the synergy between them and consequently suggest an approach based on combination of them. In addition, a systematic approach is suggested to identify required level of integrations and their corresponding approaches exemplified in a typical IT system architecture in Production Engineering.

In the domain of developing production systems, the design of a good factory is typically distributed over many disciplines and organizations to cover all involved technologies and levels of detail (process, logistics, machinery etc.). Modelling and simulation used to support the design process within each of the disciplines typically represent different contexts and perspectives. To cross the discipline borders and share experiences, to encourage innovation and make holistic decisions, one challenge is to interrelate various digital models and to reach a mutual system understanding between stakeholders. This paper presents a study based on principles from Social Science, Production Engineering, Computer Science and Information Design to address cross-disciplinary collaboration. Principles concerning visual communication and theories in regard to tangible boundary objects are used to clarify how to describe production system interdependencies in a digital factory context. Work in process of implementing a digital factory framework based on the principles is described, with a use case demonstrating the development of a digital factory for a new type of automotive vehicle.

Internet of things (IoT) in manufacturing can be defined as a future where every day physical objects in the shop floor, people and systems (things) are connected by the Internet to build services critical to the manufacturing. Smart factory is a way towards a factory-of-things, which is very much aligned with IoT. IoT not only deals with smart connections between physical objects but also with the interaction with different IT tools used within the digital factory. Data and information come from heterogeneous IT systems and from different domains, viewpoints, levels of granularity and life cycle phases causing potential inconsistencies in the data sharing, preventing interoperability. Hence, our aim is to investigate approaches and principles when integrating the digital factory, IT tools and IoT in manufacturing in a heterogeneous IT environment to ensure data consistency. In particular this paper suggests an approach to identify what, when and how information should be integrated. Secondly it suggests integration between IoT and PLM platforms using semantic web technologies and Open Services for Lifecycle Collaboration (OSLC) standard on tool interoperability.

Increasingly complex products and business models require support of increasingly complex information. In this paper we propose a new approach BIC, Business Information Context, to define contexts for accessing, viewing, and managing this complex information. BIC structures information based on key domains: business drivers, business processes, information entities, product characteristics, and information systems. We compare BIC with other and simpler approaches, like views and contexts used in the ISO 10303 (STEP) standards, design methodologies, and PLM systems. We illustrate the definition and use of BIC with an implementation of an application forprotecting a company’s intellectual property.

Design and verification of factory layout and material flow is a multidisciplinary, knowledge-intensive task which requires a collaborative framework where all specialists involved can communicate, interact, manage and visualize different models. However, the communication of digital models comes with challenges. First of all the information resides in various systems and applications, in different formats and with various levels of detail and viewpoints. Moreover, models share common properties and it is common that these properties influence each other. Hence modification of one model should be propagated to other models, which need to be coordinated.To deal with the data exchange and integration problem, information standards such as ISO 10303 have been developed. ISO 10303 (STEP) has shown a strong capability to represent rich information models in a wide variety of industrial domains for the purpose of exchanging data. However, STEP is intrinsically complex and sometimes adds unnecessary level of detail to information to be shared. On the other hand, the Open Services for Lifecycle Collaboration (OSLC) initiative provides a minimalistic set of standardized information models, focusing on the most common concepts within a particular domain. Assuming a loosely-coupled distributed architecture of tools and services, OSLC adopts the Linked Data approach to ensure data consistency across the data resources.How can we combine STEP’s rich information model for data exchange, with OSLC’s minimalistic approach for data integration?The aim of this work is to show the applicability of using these two complementary paradigms – and their corresponding standards - to support interoperability and data integration in a heterogeneous IT environment for material flow analysis and layout design. To this end, an industrial case study was implemented through the information standard STEP and the OSLC specifications to verify the suggested approach.

The complexity of product realization has increased significantly due to the requirements on ecological and social as well as economical sustainability. This has led to an increased demand on innovations concerning new materials and product- and process technologies, as well as on new business models for a better utilization of products and materials.

Most innovations occur through a learning process where various actors, individuals as well as organizations, take part. Breakthroughs do not necessarily occur within the research or development departments, they are equally likely to occur during production or utilization. The challenge thus lies in providing platforms and tools for cross-divisional, collaborative innovation and for sharing Best Practices.

This paper describes an initiative at KTH Royal Institute of Technology for supporting the integration of various company disciplines and external expertise through a collaborative framework where industry and academy can collaborate, supported by modeling, simulation and visualization during the innovation process. The approach combines theories and methods concerning innovation and digital factories and emphasizes aspects concerning learning, communication and collaboration.

Information management for manufacturing resources such as cutting tools is an important research topic in the context of cloud manufacturing. Vendors and customers usually use catalogues to communicate information for such manufacturing resource. Incompatibilities of information in syntax, semantics, and structure among supply chains often result in inefficient manual sharing and management of the catalogue information. It is difficult for cloud based applications to pool information from various sources. This communication failure calls for a system neutral solution for data modeling and exchange to enhance interoperability of the cutting tool catalogue information. Previous studies has present solutions for representation of the cutting tool information with STEP AP242 (ISO/DIS 10303-242) with semantic classification referring to a PLib (ISO 13584, Part Library) based dictionary. This approach can be extended for the catalogue modeling, due to functionalities for specification and configuration control of general product variants in the same standard. With a modeling approach with standardized information schemas, system architecture to guide implementation is proposed to enhance the communication in practice. Relative elements to represent vendors' catalogues and customers' requirements are modeled. Associations to the PLib-based dictionary complete semantics and enable information mapping between vendors and customers. Principles of the mapping are identified to facilitate implementation of related software systems. Prototypes are developed to verify the proposed system architecture. The proposed solution is promising to migrate to other types of products than cutting tools, because the data models are based on the general product models defined in AP242.

Industry needs a system neutral solution for exchange of kinematic models. In this article, the first known valid implementation of kinematic mechanisms based on ISO 10303 Standard for the Exchange of Product (STEP) is presented. The result includes an implementation framework and two developed prototypes. Two major challenges of standard-based development are identified and generalised: data integration and system integration, which are solved by the framework. The two prototypes are implemented to establish kinematic data exchange between Siemens NX® and STEP-NC Machine^TM via STEP AP214 files. Experiences of design and development of the applications are presented, and a validated case study of data exchange using the developed applications is shown. There are other attempts of using STEP as basis for modelling, but as the first valid STEP implementation on kinematics, this approach demonstrates the feasibility of pure STEP-based data exchange for kinematic mechanisms. The prototypes also show potential of utilising the framework for general standard implementations. The research is expected to motivate deeper understanding and extensive applications of the STEP standard in industry and academia.