Digital Methods for Process Development in Manufacturing and Their Relevance to Value Driven Design

This paper examines the applicability of a digital manufacturing framework to the implementation of a Value Driven Design (VDD) approach for the development of a stiffened composite panel. It presents a means by which environmental considerations can be integrated with conventional product and process design drivers within a customized, digital environment. A composite forming process is used as an exemplar for the work which creates a collaborative environment for the integration of more traditional design drivers with parameters related to manufacturability as well as more sustainable processes and products. The environmental stakeholder is introduced to the VDD process through a customized product/process/resource (PPR) environment where application specific power consumption and material waste data has been measured and characterised in the process design interface. This allows the manufacturing planner to consider power consumption as a concurrent design driver and the inclusion of energy as a parameter in a VDD approach to the development of efficiently manufactured, sustainable transport systems.

The prediction of process-induced deformation in a thermoplastic composite in support of manufacturing simulation

Digital manufacturing techniques can simulate complex assembly sequences using computer-aided design-based, as-designed' part forms, and their utility has been proven across several manufacturing sectors including the ship building, automotive and aerospace industries. However, the reality of working with actual parts and composite components, in particular, is that geometric variability arising from part forming or processing conditions can cause problems during assembly as the as-manufactured' form differs from the geometry used for any simulated build validation. In this work, a simulation strategy is presented for the study of the process-induced deformation behaviour of a 90 degrees, V-shaped angle. Test samples were thermoformed using pre-consolidated carbon fibre-reinforced polyphenylene sulphide, and the processing conditions were re-created in a virtual environment using the finite element method to determine finished component angles. A procedure was then developed for transferring predicted part forms from the finite element outputs to a digital manufacturing platform for the purpose of virtual assembly validation using more realistic part geometry. Ultimately, the outcomes from this work can be used to inform process condition choices, material configuration and tool design, so that the dimensional gap between as-designed' and as-manufactured' part forms can be reduced in the virtual environment.

Machine Learning Algorithms in Heavy Process Manufacturing

In a global economy, manufacturers mainly compete with cost efficiency of production, as the price of raw materials are similar worldwide. Heavy industry has two big issues to deal with. On the one hand there is lots of data which needs to be analyzed in an effective manner, and on the other hand making big improvements via investments in cooperate structure or new machinery is neither economically nor physically viable. Machine learning offers a promising way for manufacturers to address both these problems as they are in an excellent position to employ learning techniques with their massive resource of historical production data. However, choosing modelling a strategy in this setting is far from trivial and this is the objective of this article. The article investigates characteristics of the most popular classifiers used in industry today. Support Vector Machines, Multilayer Perceptron, Decision Trees, Random Forests, and the meta-algorithms Bagging and Boosting are mainly investigated in this work. Lessons from real-world implementations of these learners are also provided together with future directions when different learners are expected to perform well. The importance of feature selection and relevant selection methods in an industrial setting are further investigated. Performance metrics have also been discussed for the sake of completion.

Small- and medium-sized enterprises' restructuring in a context of transition: a shared process: inter-player effects on efficient boundary choice in the Argentine manufacturing sector

Includes bibliography

The "Catching up" Process of Manufacturing in East Asia

This paper examines the "catching up" process of manufacturing in East Asia within the framework of North and South location. Results of this study indicate that latecomers of the ASEAN Four and China have advanced the "catching up" process. At the same time, second-runners of the Asian NIES have more extensively increased their "catching up" with Japan. Most "catching up" was realized in a very short period in the 1990s, and the advancement of the "catching up" process has moved into various industries from nondurable products to light machinery products. However, it has not yet advanced in heavy machinery such as in the industrial machinery and machine tool industries.

Water reuse in a wet process hardboard manufacturing plant /

Mode of access: Internet.

Automotive manufacturing processes. Volume IV - metal stamping and plastic forming process. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

An application of decision process modelling to manufacturing system design

As levels of investment in advanced manufacturing systems increase, effective project management becomes ever more critical. This paper demonstrates how the model proposed by Mintzberg, Raisinghani and Theoret in 1976, which structures complicated strategic decision processes, can be applied to the design of new production systems for both descriptive and analytical research purposes. This paper sets a detailed case study concerning the design and development of an advanced manufacturing system within the Mintzberg decision model and so breaks down the decision sequence into constituent parts. It thus shows how a structured model can provide a framework for the researcher who wishes to study decision episodes in the design of manufacturing facilities in greater depth.

A process framework for selecting supply system architecture in manufacturing supply chains and networks

The process framework comprises three phases, as follows: scope the supply chain/network; identify the options for supply system architecture and select supply system architecture. It facilitates a structured approach that analyses the supply chain/network contextual characteristics, in order to ensure alignment with the appropriate supply system architecture. The process framework was derived from comprehensive literature review and archival case study analysis. The review led to the classification of supply system architectures according to their orientation, whether integrated; partially integrated; co-ordinated or independent. The classification was combined with the characteristics that influence the selection of supply system architecture to encapsulate the conceptual framework. It builds upon existing frameworks and methodologies by focusing on structured procedure; supporting project management; facilitating participation and clarifying point of entry. The process framework was initially tested in three case study applications from the food, automobile and hand tool industries. A variety of industrial settings was chosen to illustrate transferability. The case study applications indicate that the process framework is a valid approach to the problem; however, further testing is required. In particular, the use of group support system technologies to support the process and the steps involving the participation of software vendors need further testing. However, the process framework can be followed due to the clarity of its presentation. It considers the issue of timing by including alternative decision-making techniques, dependent on the constraints. It is useful for ensuring a sound business case is developed, with supporting documentation and analysis that identifies the strategic and functional requirements of supply system architecture.