A framework for integrating manufacturing process design and analysis

Product design and evaluation requires a broad and varied set of information and analysis tools. Yet effective design and evaluation of a product during its design phase is critical if production costs are to be minimized. A system is described that integrates product design specifications with material and process databases, and a simulation-based analysis module. The system allows product designs to be evaluated in terms of economic and technical criteria, and to identify the best production environment.     

Population evolution analysis in collective intelligence design ecosystem

The Collective Intelligent Design Ecosystem is a dynamic ecosystem founded on an online design platform that leverages collective intelligence to support the creation of novel products. The system's primary components are its users and designers. Maintaining the system's sustainability requires expanding the scale of the designer and user populations as it evolves to stabilize. However, the unity of ecological interactions between various populations is fragmented in contemporary studies of population-scale evolution, and the parameterization of evolutionary models is illogical. To overcome this gap, this research provides a population evolution model of collective intelligent design incorporating participants' intra- and interspecific ecological connections. The model's validity is verified by the evolutionary simulation of 110 designers and 5990 users of China's largest collective intelligence design platform, the Zhubajie platform, and illuminating conclusions are in turn drawn from this simulation. First, the designer's influence on the user is greater than the user's impact on the designer. Second, keeping current members engaged is more crucial to the system's viability than luring in new ones. Third, fostering collaboration among designers while retaining user competitiveness can promote system growth. Fourth, decreasing the reliance between particular designers and users might hasten the system's evolution.     

Work design and analysis for space-based manufacturing: a case analysis of initial design issues

The purpose of the present research was to investigate the nature of potential manufacturing tasks humans may execute in a space environment. The success of space-based manufacturing (SBM) is suggested to be a precursor to permanent human presence in space. A working hypothesis for this study was that human work in the SBM environment would be substantially different from terrestrial manufacturing work. To investigate this hypothesis, a case analysis approach was developed that employed a function allocation and task analysis of a representative SBM process: the production of tailored industrial crystals. This research approach was chosen as the current state of engineering design for SBM is in the conceptual and early flow sheeting phases of a system life cycle. Results of the task analysis and function allocation process suggest response to corrective maintenance functions and to abnormal system conditions should be allocated to humans as opposed to automation. These results are discussed in relation to human factors engineering challenges associated with long-duration human presence in an SBM environment.     

Work design and analysis for space-based manufacturing: a case analysis of initial design issues

The purpose of the present research was to investigate the nature of potential manufacturing tasks humans may execute in a space environment. The success of space-based manufacturing (SBM) is suggested to be a precursor to permanent human presence in space. A working hypothesis for this study was that human work in the SBM environment would be substantially different from terrestrial manufacturing work. To investigate this hypothesis, a case analysis approach was developed that employed a function allocation and task analysis of a representative SBM process: the production of tailored industrial crystals. This research approach was chosen as the current state of engineering design for SBM is in the conceptual and early flow sheeting phases of a system life cycle. Results of the task analysis and function allocation process suggest response to corrective maintenance functions and to abnormal system conditions should be allocated to humans as opposed to automation. These results are discussed in relation to human factors engineering challenges associated with long-duration human presence in an SBM environment.     

Cloud manufacturing: Strategic vision and state-of-the-art

Cloud manufacturing, a service oriented, customer centric, demand driven manufacturing model is explored in both its possible future and current states. A unique strategic vision for the field is documented, and the current state of technology is presented from both industry and academic viewpoints. Key commercial implementations are presented, along with the state of research in fields critical to enablement of cloud manufacturing, including but not limited to automation, industrial control systems, service composition, flexibility, business models, and proposed implementation models and architectures. Comparison of the strategic vision and current state leads to suggestions for future work, including research in the areas of high speed, long distance industrial control systems, flexibility enablement, business models, cloud computing applications in manufacturing, and prominent implementation architectures.     

An interoperable solution for Cloud manufacturing

Cloud manufacturing is a new concept extending and adopting the concept of Cloud computing for manufacturing. The aim is to transform manufacturing businesses to a new paradigm in that manufacturing capabilities and resources are componentized, integrated and optimized globally. This study presents an interoperable manufacturing perspective based on Cloud manufacturing. A literature search has been undertaken regarding Cloud architecture and technologies that can assist Cloud manufacturing. Manufacturing resources and capabilities are discussed in terms of Cloud service. A service-oriented, interoperable Cloud manufacturing system is proposed. Service methodologies are developed to support two types of Cloud users, i.e., customer user and enterprise user, along with standardized data models describing Cloud service and relevant features. Two case studies are undertaken to evaluate the proposed system. Cloud technology brings into manufacturing industry with a number of benefits such as openness, cost-efficiency, resource sharing and production scalability.     

Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation

Cloud-based design manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are enabled to configure, select, and utilize customized product realization resources and services ranging from computer-aided engineering software to reconfigurable manufacturing systems. An ongoing debate on CBDM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, communication and collaboration processes, crowdsourcing processes, information and communication infrastructure, programming models, data storage, and new business models pertaining to CBDM. One question, in particular, has often been raised: is cloud-based design and manufacturing actually a new paradigm, or is it just “old wine in new bottles”? To answer this question, we discuss and compare the existing definitions for CBDM, identify the essential characteristics of CBDM, define a systematic requirements checklist that an idealized CBDM system should satisfy, and compare CBDM to other relevant but more traditional collaborative design and distributed manufacturing systems such as web- and agent-based design and manufacturing systems. To justify the conclusion that CBDM can be considered as a new paradigm that is anticipated to drive digital manufacturing and design innovation, we present the development of a smart delivery drone as an idealized CBDM example scenario and propose a corresponding CBDM system architecture that incorporates CBDM-based design processes, integrated manufacturing services, information and supply chain management in a holistic sense.     

Simulation for manufacturing system design and operation: Literature review and analysis

This paper provides a comprehensive review of discrete event simulation publications published between 2002 and 2013 with a particular focus on applications in manufacturing. The literature is classified into three general classes of manufacturing system design, manufacturing system operation, and simulation language/package development. The paper further categorizes the literature into 11 subclasses based on the application area. The current review contributes to the literature in three significant ways: (1) it provides a wide coverage by reviewing 290 papers; (2) it provides a detailed analysis of different aspects of the literature to identify research trends through innovative data mining approaches as well as insights derived from the review process; and (3) it updates and extends the existing classification schemes through identification and inclusion of recently emerged application areas and exclusion of obsolete categories. The results of the literature analysis are then used to make suggestions for future research.     

Natural intelligence in design and manufacturing

This paper describes a hybrid intelligent system to implement and experiment with the “automated factory”. The objective of the project is to develop and test a new method of automating design and manufacturing by utilizing natural intelligence or more specifically, techniques such as fuzzy logic, Fuzzy Associative Memory (FAM), Backpropogation neural networks (BP), and Adaptive Resonance Theory (ART1).     

Coordinate tolerancing in design and manufacturing

Design and/or functional dimensions and tolerances do not always coincide with the coordinate machining axes. For manufacturing reasons, these dimensions and tolerances must often be transferred to the orthogonal datum system of the particular application. Whereas the derivation of the new dimensions or coordinates does not present any major problems this is not the case with new coordinate tolerances. The tolerance transfer principle alone is not sufficient for their systematic evaluation. Additional constraints towards an optimized problem approach must be introduced. In this paper, an analysis of the 3D coordinate tolerance problem is presented in conjunction with the requirements of the tolerance transfer principle and the limitations imposed by the accuracy-related manufacturing cost and process and machine tool capabilities. The application of the procedure developed for the evaluation of coordinate tolerances is further demonstrated in a case study.     

A methodology of forming manufacturing cells using manufacturing and design attributes

This study develops a methodology for forming machine cells using part's design and manufacturing dissimilarities. The proposed methodology is divided into two sequential phases. In phase I parts are grouped into families based upon their design and manufacturing attributes. In phase II, the machines are grouped into manufacturing cells based on relevant operational costs and the various cells are assigned part families using an optimization technique.     

Part design using manufacturing features

This paper presents a methodology by which manufacturability data is used to drive the design process. The system allows a designer to determine the features to be considered. He provides the basic geometric parameters for each feature and passes them to the modeling system for instantiations. Tolerances and surface finish allow the system to derive manufacturing implications used by the designer to review the design. The physical parameters, in addition to the processing information, lead to an integrated model which may be used by both the designer and the manufacturing personnel. This procedure may be invoked at any level of the design process and contribute to a final manufacturable design. The philosophy employed in the development of this work is to define manufacturing features as instances of generic ones with specific properties and processing methods. The design features obtain their geometric superclasses from a commercially available package of solid primitives thus allowing for the part to be graphically displayed.     

An organism-oriented modeling approach to support the analysis and design of intelligent manufacturing systems

In this paper a generic macroscopic object, termed an organism, is introduced. An organism defines a high-level modeling object that has the capabilities for organizational networking, standardization or characteristics specifications, decoupling of editing and visualization as well as temporal management. Organism-oriented models inherit from their parent object-oriented and object/agent-oriented models a simplified representation of the manufacturing entities as well as a capacity for many levels of abstraction. Moreover, the organism-oriented modeling approach enriches these models by not only considering basic manufacturing objects and agents, but also the fact that each of these objects and agents may itself be an organization and also part of one or several organizations. The paper first surveys some of the current approaches used for modeling and analysing manufacturing systems: structured analysis, Petri nets, object and object/ agent models. The object model behind the organism-oriented modeling approach is then presented and its application to a manufacturing case is illustrated.     

Ubiquitous manufacturing system based on Cloud: A robotics application

Modern manufacturing industry calls for a new generation of production system with better interoperability and new business models. As a novel information technology, Cloud provides new service models and business opportunities for manufacturing industry. In this research, recent Cloud manufacturing and Cloud robotics approaches are reviewed. Function block-based integration mechanisms are developed to integrate various types of manufacturing facilities. A Cloud-based manufacturing system is developed to support ubiquitous manufacturing, which provides a service pool maintaining physical facilities in terms of manufacturing services. The proposed framework and mechanisms are evaluated by both machining and robotics applications. In practice, it is possible to establish an integrated manufacturing environment across multiple levels with the support of manufacturing Cloud and function blocks. It provides a flexible architecture as well as ubiquitous and integrated methodologies for the Cloud manufacturing system.     

Simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection

Tolerance specification is an important part of mechanical design. Design tolerances strongly influence the functional performance and manufacturing cost of a mechanical product. Tighter tolerances normally produce superior components, better performing mechanical systems and good assemblability with assured exchangeability at the assembly line. However, unnecessarily tight tolerances lead to excessive manufacturing costs for a given application. The balancing of performance and manufacturing cost through identification of optimal design tolerances is a major concern in modern design. Traditionally, design tolerances are specified based on the designer’s experience. Computer-aided (or software-based) tolerance synthesis and alternative manufacturing process selection programs allow a designer to verify the relations between all design tolerances to produce a consistent and feasible design. In this paper, a general new methodology using intelligent algorithms viz., Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi Objective Particle Swarm Optimization (MOPSO) for simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection is presented. The problem has a multi-criterion character in which 3 objective functions, 3 constraints and 5 variables are considered. The average fitness factor method and normalized weighted objective functions method are separately used to select the best optimal solution from Pareto optimal fronts. Two multi-objective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the strength of Pareto optimal fronts. Two more multi-objective performance measures namely optimiser overhead and algorithm effort are used to find the computational effort of NSGA-II and MOPSO algorithms. The Pareto optimal fronts and results obtained from various techniques are compared and analysed.     

Adaptability analysis of design for additive manufacturing by using fuzzy Bayesian network approach

The rapid development of Additive Manufacturing (AM) has been conspicuous and appealing towards manufacturing end-use products and components over the past decade. The continual advancement of AM has brought many advantages such as personalization and customization, reduction of material waste, cutting off the existence of special tooling during fabrication, etc. However, the AM approach has its limitations, such as a lack of knowledge of AM process activities and the progressive industrialization of AM, which makes the design process activities unstable, unpredictable, and have a limited effect. The concept of “design for AM (DFAM)” is increasing, which means we have the opportunity to concentrate almost totally on product functioning. Therefore, the entire design paradigm must be revised to accommodate new production capabilities, geometries, and parameters to avoid molding or machine tooling technology constraints. Few studies have attempted to provide systematic and quantitative knowledge of the relationship between these elements and the feasibility of the design process, making it difficult for designers to assess and control AM industrialization. For this reason, DFAM is needed to reform AM from rapid manufacturing to a mainstream manufacturing method. This paper put forward a framework based on the Fuzzy Bayesian Network (FBN) for DFAM decision-making. Twenty impact factors were encapsulated from experts’ experience and existing literature to investigate the potential adaptability of DFAM. The proposed approach uses expert knowledge and Fuzzy Set Theory (FST) presented with Triangular Fuzzy Numbers (FFN) to perceive the uncertainties. The Bayesian Network (BN) captures the causal relationships and dependencies among the impact components and analyzes the DFAM adaptability for robust probabilistic reasoning. A robot arm claw was used to show the effectiveness of our approach. The results showed that FBN could be used to guide DFAM adaptability in the manufacturing industry.