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The purpose of this paper is to present Design Rules for additive manufacturing and a method for their development.

First, a process-independent method for the development of Design Rules was worked out. Therefore, geometrical standard elements and attributes that characterize the elements’ shapes have been defined. Next, the standard elements have been manufactured with different attribute values with Laser Sintering, Laser Melting and Fused Deposition Modeling, and their geometrical quality was examined. From the results, Design Rules for additive manufacturing were derived and summarized in a catalogue.

Due to the process independent method, Design Rules were developed that apply for the different considered additive manufacturing technologies equally. These Design Rules are completely function-independent and easily transferable to individual part designs.

The developed Design Rules can only apply for the considered boundary conditions. To extend the Design Rules’ validity, their applicability should be proven for other boundary conditions.

The developed Design Rules practically support the design of technical parts. Additionally they can be used for training and teaching in the field of “design for additive manufacturing”.

The developed Design Rules constitute a first step toward general Design Rules for Additive Manufacturing. Thus, they might form a suitable basis for further scientific approaches, and the Design Rules can be used to set up teaching documentations for lessons and seminars.

As the technology matures, design rules for additive manufacturing (AM) can help ensure manufacturability, which can be viewed as compatibility between designs and the fabrication processes that produce those designs. Though often informal, current rules frequently provide direct guidelines or constraints for designing AM-destined parts. The aim of this paper is to standardize how design rules are developed and conveyed in AM by presenting design rules as sets of modular components and associated formalisms.

The proposed methodology decomposes fundamental geometry, process and material relationships into reusable modules. Independent of context, modular representations can be more easily interpreted and efficiently implemented than current one. By providing task-specific context, components are specialized to represent process-specific parameters for different AM builds and processes. This method of specialization enables designers to reconfigure design rules, rather than create new rules from scratch, thus preserving fundamental AM principles while supporting customization and explicit representation.

Modularity and formalisms provide both structure for the generalizations and a means to tailor that structure for a specific process, machine or build. The adoption of principles and formalisms that allow us to modify, extend, reconfigure or customize generalized rules as needed – instinctively and deliberately.

This method of specialization enables designers to reconfigure design rules, rather than create new rules from scratch, thus preserving fundamental AM principles while supporting customization and explicit representation.

The purpose of this paper is to present an information model (ontology) for design‐for‐manufacturing (DFM) problems, where parts are to be manufactured using an additive manufacturing process. DFM problem formulation is often challenging since the formulation step requires both design and manufacturing process knowledge. The ontology also captures some relationships that model how that manufacturing knowledge applies to part designs. The ontology is implemented and serves as a repository of DFM problems that are available for reuse.

The ontology is encoded using a description logic (DL) known as ALE. Using this ontology, a designer can retrieve archived DFM problems that are similar to a problem being formulated. DLs are a subset of first‐order logic that have been used for information modeling in several application areas, including engineering information management. They are used typically to construct classification hierarchies that can be efficiently searched.

The paper demonstrates that the DL model is correct by showing that the classification hierarchies that are computed match our DFM ontology. Retrieval of DFM problems is demonstrated using a prototype implementation of our ontology. Examples are taken from the area of design for manufacture using the stereolithography process.

The domain of the ontology is limited to additive manufacturing processes. Only DFM problems related to the determination of design parameters (e.g. dimensions) were within the scope of this work.

No ontology for DFM problems has been presented previously. Implementation of the ontology using DL is also original.

The purpose of this study is to characterize construction management research at the interface of explanatory science and design science.

The dual nature of construction management research is analyzed by relating this field of research to natural science, design science and its interface. Research at the interface of explanatory science and design science is characterized by identifying studies published on this interface in high quality construction management journals.

Research at this interface should focus on technological rules developed through testing in practical contexts as in design science as well as grounding in the explanatory sciences. The nature of testing technological rules is highly similar to the replication logic recommended for comparative case studies.

Developing and testing technological rules combines the design science and the explanatory science mode of knowledge production in construction management research, while it also respects some of the methodological differences between the two modes.

Developing and testing technological rules is the common ground on which research in construction management practice and research can meet and reduce the relevance gap between science and the world of practice.

The purpose of this paper is to present a Design for Additive Manufacturing (DfAM) methodology that connects several methods, from geometrical design to post-process selection, into a common optimisation framework.

A design methodology is formulated and tested in a case study. The outcome of the case study is analysed by comparing the obtained results with alternative designs achieved by using other design methods. The design process in the case study and the potential of the method to be used in different settings are also discussed. Finally, the work is concluded by stating the main contribution of the paper and highlighting where further research is needed.

The proposed method is implemented in a novel framework which is applied to a physical component in the case study. The component is a structural aircraft part that was designed to minimise weight while respecting several static and fatigue structural load cases. An addition goal is to minimise the manufacturing cost. Designs optimised for manufacturing by two different AM machines (EOS M400 and Arcam Q20+), with and without post-processing (centrifugal finishing) are considered. The designs achieved in this study show a significant reduction in both weight and cost compared to one AM manufactured geometry designed using more conventional methods and one design milled in aluminium.

The method in this paper allows for the holistic design and optimisation of components while considering manufacturability, cost and component functionality. Within the same framework, designs optimised for different setups of AM machines and post-processing can be automatically evaluated without any additional manual work.

With the advent of the era of Big Data, the scale of knowledge graph (KG) in various domains is growing rapidly, which holds huge amount of knowledge surely benefiting the question answering (QA) research. However, the KG, which is always constituted of entities and relations, is structurally inconsistent with the natural language query. Thus, the QA system based on KG is still faced with difficulties. The purpose of this paper is to propose a method to answer the domain-specific questions based on KG, providing conveniences for the information query over domain KG.

The authors propose a method FactQA to answer the factual questions about specific domain. A series of logical rules are designed to transform the factual questions into the triples, in order to solve the structural inconsistency between the user’s question and the domain knowledge. Then, the query expansion strategies and filtering strategies are proposed from two levels (i.e. words and triples in the question). For matching the question with domain knowledge, not only the similarity values between the words in the question and the resources in the domain knowledge but also the tag information of these words is considered. And the tag information is obtained by parsing the question using Stanford CoreNLP. In this paper, the KG in metallic materials domain is used to illustrate the FactQA method.

The designed logical rules have time stability for transforming the factual questions into the triples. Additionally, after filtering the synonym expansion results of the words in the question, the expansion quality of the triple representation of the question is improved. The tag information of the words in the question is considered in the process of data matching, which could help to filter out the wrong matches.

Although the FactQA is proposed for domain-specific QA, it can also be applied to any other domain besides metallic materials domain. For a question that cannot be answered, FactQA would generate a new related question to answer, providing as much as possible the user with the information they probably need. The FactQA could facilitate the user’s information query based on the emerging KG.

In a recent edition of the nation's favourite soap, Coronation Street, a small incident occurred which illustrated in a nutshell the problems facing the deviser of an industrial design in seeking to protect that design from being copied. Angie, a student of fashion design at the local polytechnic put on a successful show of her designs. Emboldened by the favourable reception she set out a couple of days later for an appointment with a local dress manufacturer to try and sell her designs. She returned a few hours later in tears and with hopes dashed. She had arrived at the firm only to discover that her designs were already being made up into dresses. The designs had been copied at the show and already sold to or copied by them. The incident was not without its silver lining in that in getting drunk to forget the whole sad affair this lead to a romantic interlude with fellow lodger, Curley Watts! It is the purpose of this article to examine the main strands of protection for industrial designs and to look at a proposed new European Community Design Law which has recently been published by the prestigious Max Planck Institute for Foreign and International Patent, Copyright and Competition Law (Munich, 1991). This proposal is being put to the EC Commission as the basis for an EC Regulation.

Investigates the trade‐off between the average throughput rate and the average systems time using kanban discipline. Considers a multistage serial production line system with materials in the system controlled by kanban discipline. Presents simulation results to evaluate the production system performance in terms of the average throughput rate and the average system time for a fixed total number of kanbans over a given number of serial workstations. Constructs and compares efficient allocation sets for three and four workstations that are generated by kanban discipline for two processing time distributions, namely, uniform and exponential distributions. Based on the simulation results from three and four work‐stations, develops a general design rule to maximize the average throughput rate and to minimize the average system time. Analyses five and six workstations using the general design rule. Tests the validity of the general design rule by considering five and six workstations with a different number of kanbans. The results show that most of the efficient sets generated by the design rule are identical to those generated by enumerating all combinations of kanban allocations. However, using the general design rule reduces the simulation work tremendously.

Inter‐organizational innovation networks provide opportunities to exploit complementary resources that reside beyond the boundary of the firm. The shifting locus of innovation and value creation away from the “sole firm as innovator” poses important questions about the nature of these resources and the capabilities needed to leverage them for competitive advantage. The purpose of this paper is to describe research into producing design‐oriented knowledge, for configuring inter‐organizational networks as a means of accessing such resources for innovation.

This exploratory investigation conflates emerging constructs and themes analytically induced from a systematic survey of 142 scholarly and practitioner articles and 45 expert interviews with senior professionals operating in the biopharmaceuticals industry.

The findings identify seven theoretically and empirically grounded technological rules associated with effective inter‐organizational networking for innovation. They embody evidence ex post of networking theory and practice. Based on van Aken's seminal work, they comprise design‐oriented knowledge to provide a solution architecture of viable action options for managers, a priori, to purposefully design innovation networks. Collectively these rules represent a tentative taxonomy, a means of classifying design principles, to assist managers in navigating their decision‐making processes.

This study demonstrates the need for explicit design‐oriented knowledge for configuring inter‐organizational networks. Finally, the implications of the findings for strategic management theory are discussed from a dynamic capabilities view. The significance of a dynamic capability which addresses the renewal of network‐specific resources is highlighted.

Biologically inspired techniques like cellular automata (CA) are gaining nowadays attention of designers. This is because they are effective, do not require gradient information, and one can easily combine this type of algorithm with any finite element structural analysis code. The purpose of this paper is to develop a CA algorithm based on novel local rules oriented at solving compliance-based topology optimization problems.

The design domain is divided into lattice of cells, states of which are updated synchronously. The proposed rules include information coming from an individual cell and from its neighborhood, and by introducing weighting parameters allow to control and modify topology generation process.

The performance of the developed algorithm is very satisfactory, and a comparison with results of other authors, obtained with the use of various optimization techniques, shows efficiency of the present topology generation process. The results found within approach of this paper are in a good agreement with the ones already reported, both for optimal topologies and values of minimal compliance, which in some cases are found even improved.

The algorithm presented in the paper is quite general what allows its easy application to engineering design problems. Moreover, the local update rules are simple, so they can be easily implemented into professional FEM analysis codes, as an efficient add-on module for topology optimization.

The main advantage of the developed algorithm is that it is a fast convergent technique and usually requires far less iterations as to achieve the solution, when compared to other approaches. What is also important does not require any additional density filtering. It also overcomes some drawbacks of traditional approaches so that changing mesh density does not influence resulting topologies and solutions are free from checkerboard effect.