For the past decade, lean manufacturing has reshaped manufacturing processes at numerous corporations. Even organizations that were already conscious of quality, cost, and delivery have benefited tremendously from these principles. The foundation of lean manufacturing is the elimination of nonvalue added elements, waste. There are three important value streams in the realization of any product — the engineering value stream, the manufacturing value stream, and the information management value stream. This paper focuses on the engineering value stream. The methods of lean manufacturing can be applied for waste elimination in engineering. The dissemination of lean manufacturing principles into engineering would multiply the significant benefits already derived by embracing lean in the manufacturing part of the enterprise. Little attention has been given to a systematic method of lean engineering that aims not only at reducing engineering lead-time, but also at identifying, measuring, and eliminating waste in engineering processes. Engineering organizations lack a basic methodology for waste elimination. This paper proposes a systematic, ten-step method for engineering waste elimination. Such a systematic method will help engineering organizations systematically identify, measure, and eliminate engineering wastes from all engineering processes. The systematic method is then used to demonstrate the elimination of waste in engineering through its application to the manufacturing equipment installation — a manufacturing engineering process. In today’s competitive world, the ability to bring better products to market faster has become the focal point of competition. The use of this systematic method for engineering waste elimination holds significant promise for organizations wanting to outperform their competitors on quality, cost, and delivery.

This report describes a number of product development life-cycle approaches theorized academically and observed in industry. The design process is an important part of the product life-cycle as decisions made then have the greatest impact on product quality and cost. Process formalization and improvement are a necessary step in enabling product development robustness and error-proofing. Process models such as gate approaches or phased review processes are used to structure and focus the process. Through benchmarking organizations such as General Electric, ABB, and NASA, comparisons on the focus and effectiveness of various methods can be made. The paper concludes with lessons on the implementation of such process models and future research to better implement and improve them.

Robotized filament winding technology involves a robot that winds a roving impregnated by resin on a die along the directions of stresses the work-piece is submitted to in exercise. The robot moves a deposition head along a winding trajectory in order to deposit roving. The trajectory planning is a very critical aspect of robotized filament winding technology, since it is responsible for both the tension constancy and the winding time. The present work shows an original method to plan the winding trajectory of structural parts whose shape is obtained by sweeping a full section around a 3D closed not auto-intersecting curve. The trajectory is defined by offsetting this 3D curve of the distance needed to keep the tension on roving near to the value chosen to assure good mechanical performances of the manufactured composite parts. This trajectory allows to satisfy the constraints on the geometrical parameters of the winding trajectory (i.e. safety distance and winding angle) that assure to keep the value of tension near to the nominal one during winding. This means to assure an acceptable quality of the manufactured composite parts. Moreover, the planned trajectory allows to decrease strongly the winding time, when compared to the alternative methods of the trajectory planning.

In product development, engineers first collect customer needs and then group similar needs to identify a small number of representative needs. Engineers transfer these representative needs to target product requirements and develop products that fulfill these requirements. In grouping similar needs, engineers use affinity diagram, which is a popular consensus-based method, or subjective clustering, which is a statistical method. This paper applies bootstrap to subjective clustering in order to assist engineers make an inference about the population cluster of customer needs. This paper presents a procedure for bootstrap application to subjective clustering, a preliminary experiment, and an illustrative example.

Design for assembly (DFA) is an important principle in product development for cost saving and product improvement. Previous DFA research mainly concentrated on a forward process from product design to final assembly planning, which neglects the backward validation using assembly planning to verify the product design. This paper presents an industrial case study of product design for assembly. It uses well-established DFA concepts and integrates the design analysis and a genetic algorithm in product assembly planning to achieve a complete application of DFA in product development. Criteria of the design analysis are established using DFA rules, the assembly efficiency and the connector-based fitness function. Product design alternatives and assembly sequences are considered simultaneously as a basis of the product design for assembly execution.

A product assembly or disassembly is completed by means of proper tools. The selection of feasible tools is an important process in planning a complete assembly or disassembly sequence. A key tooling consideration in assembly or disassembly planning is to reason the available space for a tool application during the assembly or disassembly of a product. Currently, assembly tool reasoning about space mainly depends on simulation-based or user-interactive approaches because of its computational complexity. These approaches are not proper in dealing with various what-if scenarios regarding assembly or disassembly planning in a rapid product development. They also depend on users’ expertise or experience in assembly or disassembly. This paper presents an efficient method of the geometric accessibility analysis for fast assembly tool reasoning. Techniques described in the paper are advantageous not only in the aid of generating a complete assembly or disassembly plan but also in the efficient support of such systems as computer-aided assembly planning (CAAP), design for manufacturing (DFM), design for assembly (DFA), design for disassembly (DFD), and computer-aided tool selection (CATS).

Low-density cellular materials, metallic bodies with gaseous voids, are a unique classification of material that have high strength, good energy absorption characteristics, good thermal and acoustic insulation properties, accompanied by an extremely low mass. Unfortunately, current cellular material, manufacturing processes severely limit a designer’s ability to control the part mesostructure, the material composition, and the part macrostructure. In this paper, the capability of existing commercially available Additive Manufacturing technologies to manufacture cellular materials is evaluated using the Preliminary Selection Decision Support Problem. Through this evaluation, the technologies that are most suitable for this class of materials are chosen. More importantly, the general material processing issues of these technologies are identified. Promising technical directions are also posed as a means of addressing the limitations of the currently available processing techniques.

This paper presents a method for modifying the design of the new part for the maximum utilization of existing production lines dedicated to other products. The method takes as inputs a nominal part design and the process information of the (potentially multiple) existing line(s), and produces a modified part design and a process sequence of the new part that maximizes the utilization of available manufacturing processes in the existing lines or equivalently minimizes the addition of new processes dedicated to the new product. The problem is formulated as mixed discrete-continuous multi-objective optimization and a multi-objective genetic algorithm is used to generate Pareto optimal designs. A case study on the production of a new machine bracket considering two available production lines is presented.

In this paper we investigate the suitability of the GapSpace assembly analysis method [1] for assemblies in which there is interference between the components. Of particular interest are assemblies in which there are several sets of features that can influence the final location of the parts, once assembled. Our analysis includes using the finite element method to estimate the work required for assembly and the total strain energy in the components after assembly is complete. We then examine how these values can be predicted for different part geometries that can arise for a particular specification of part tolerances. The goal of this work is to provide fast approximations of force/work/energy calculations for designers of assemblies in which interference is required.

This paper presents the design of new joints, heat-reversible snaps, which allow easy, non-destructive, and clean detaching between internal frames and external panels in automotive bodies. It is expected to dramatically reduce the end-of-life environmental impacts of the aluminum space frame bodies, which currently suffer from poor material recyclability. While the assembly process is analogous to normal locator-snap systems, the heat-reversible snaps can be unlocked non-destructively upon heating the panel at a certain location, via the non-uniform thermal deformation of the panel. The optimum number and locations of the locators on the given panel are found based on the equivalent springs that represent the stiffness of the locator. Then, the locations of snaps and heating that ensure unlocking upon heating of the minimum area on the panel are obtained. Finally, a case study on an automotive fender panel assembly is discussed.

It has been commonly accepted in CAD/CAM that for machining code generation, only the surface information of the to-be-manufactured areas is needed. Therefore most of the CAM softwares are predominantly surface modelers and generate toolpath simply based on the geometries and topologies of the desired surfaces. But considering the whole volume that needs to be removed from the stock, we believe it is more beneficial to depict the entire cut volume rather than just specify the desired surfaces. In this paper, a boundary conformed parametric implicit solid modeler is introduced. This modeler contains the entire geometric information of the enclosed solid implicitly. Any solution of this implicit modeler could results into the interior parametric-object space mapping. A Laplace-based solution is developed for the interior of this modeler, consequently the surface-morphing concept according to this Laplace solution is used for automatic tool-path generation. This morphing technology can be applied to both rough cutting and finish cutting in a unified process.

Environmental consciousness in manufacturing has increased in recent years. In order to maximize the potential of this approach, closed-loop manufacturing systems, where products are made from used products, reused parts and materials from market, as well as new materials, should be established. For factories, the often-complicated fluctuations associated with volumes, quality, and supply of these reused resources make effective management of these factories considerably difficult. The purpose of this study was thus to derive rules and conditions for operating such factories efficiently by simulating processes considering the fluctuations of material supply. Simulation results show that fluctuations in operation time during recovery processes have a significant impact on the smoothness of flow through the entire system. Also, variations in the lifetime of each part in a product is responsible for low saturation rates of market demand, although these variations can level the load of recovery processes and decrease inventory levels of the inverse processes.

Different studies are required during the design process to improve the performance and quality of complex mechanical systems. Such systems usually contain deformable parts, which complex behavior is a critical factor that must be taken into account during the design, assembly/disassembly (A/D), ergonomics evaluations of a product. Virtual Reality (VR) proposes the designer specific functions to study efficiently complex systems: interaction with a virtual part, visual/force feedback, real-time multi criteria analysis of A/D. However, the quality of virtual simulations like A/D of flexible parts depends on input data. The aim of this work is to discuss main input data required for realistic simulations of virtual A/D of flexible parts. Some input parameters are used by a behavior model of flexible beams coupled to virtual A/D. The incorporation of mechanical models implies the use of material properties, which are hard to set up for multi-material flexible parts. This paper proposes a method to determine quickly a material characteristic of such parts for realistic virtual A/D simulations. Examples of law behavior definition as well as A/D simulation of a flexible part using the proposed approach are presented.

Rapid Prototyping (RP) is the process of building three-dimensional objects, in layers, using additive manufacturing. Rapid Manufacturing (RM) is the use of RP technologies to manufacture end-use, or finished, products. At small lot sizes, such as with customized products, traditional manufacturing technologies become infeasible due to the high costs of tooling and setup. RM offers the opportunity to produce these customized products economically. Coupled with the customization opportunities afforded by RM is a certain degree of uncertainty. This uncertainty is mainly attributed to the lack of information known about what the customer’s specific requirements and preferences are at the time of production. In this paper, we present an overall method for selection of a RM technology under the geometric uncertainty inherent to mass customization. Specifically, we define the types of uncertainty inherent to RM (epistemic), propose a method to account for this uncertainty in a selection process (interval analysis), and propose a method to select a technology under uncertainty (Hurwicz selection criterion). We illustrate our method with an example on the selection of an RM technology to produce custom caster wheels.

In product development, firms choose product concepts in the conceptual design phase and develop final products from the chosen concepts. Concept selection is one of the most difficult decisions in product development since it involves large degrees of uncertainties. This paper presents a framework for decision-analytic concept selection and information gathering in a public project, in which the government has an option to cancel the project if the cost of the project exceeds the budget. In this framework, a customer (e.g., the government) has an option to cancel the project instead of a decision-maker (e.g., a national laboratory). In information gathering, this paper presents, first, sensitivity analysis that enables engineers to investigate whether it is beneficial to collect additional information about uncertainties, and second, the value of perfect information in determining the maximum monetary resource they should spend for such activity. Finally, an illustrative example demonstrates decision-analytic concept selection, sensitivity analysis, and the value of perfect information for a next generation linear collider.

Industry and students clamor for increased training related to engineering design and analysis methods. Often, students are hired based on the suite of software packages and Design for Manufacturing methods with which they are familiar as opposed to their knowledge of the fundamentals and their ability to formalize and solve open ended design problems. In support of a domain-centric design education, some of the trends that are driving the increased domain emphasis in design education are documented including decreasing computing cost, decreasing communication costs, and decreasing engineering tenures. The paper then discusses the ramifications of these trends on design education and design practice as measurable by the availability of the mechanical engineering design curricula, design publications, and design patents. Finally, a domain-centric design education paradigm is proposed that suggests the differentiation of Mechanical Engineering programs through the replacement of traditional machine and product design courses with domain-specific courses with increased technical specialty.

This paper describes a greyscale “painting system” that enables the physical reproduction of digital texture maps on arbitrary 3D objects by selectively exposing “pixels” of photographic emulsion with a robot mounted light source. The system requires no bespoke production tooling and fills an automation gap in rapid prototyping and manufacturing technology that is currently occupied by hand painting. After reviewing existing methods of “decorating” 3D components, the properties of photographic emulsion are introduced and the nature of the rendering process’ pixels discussed. A proposed path planning algorithm, used to derive both the robot’s movement and the exposure times directly from a VRML representation, is then presented. Next, there is a description of the system’s implementation and a discussion of the results obtained from rendering images on the surface of a test object. Finally, a discussion of the system’s potential and limitations is given.

In present era of environmentally conscious manufacturing, End-of-life (EOL) product disassembly is increasingly used for the product recovery process. However, the low efficiency in disassembly process put a great challenge in front of manufacturers to achieve the environmental goals set for the product. To achieve the efficient utilization in part recycling processes at the end of its life, disassembly line has important role to play. Thus, much emphasis is given by the research community to reduce the company reliance on the availability of human experts to improve the intelligence in the disassembly process. This research aims to optimize the number of machine required to disassemble the parts in a disassembly line. The complexity while disassembly increases in case of defects in the tasks to be allocated on the workstation. In this paper an evolutionary approach named Psycho-Clonal is proposed to solve the disassembly line-balancing problem in the presence of task failure. The proposed algorithm is inspired by artificial immune systems (AIS), which is further enhanced by the authors by incorporating Maslow’s need hierarchy theory work as a meta-heuristic. The main attributes of the algorithm are the various need levels, immune memory, and affinity maturation. Need levels incorporated in the algorithm help in satisfying the model constraints, thus empowering the algorithm to work for a multi-objective, multi-constraints problem. Immune memory helps in preserving the best solution and affinity maturation helps in exploring and exploiting the search space.

In pursuit of the most competitive advantages in modern dynamic business environment, companies have recognized the importance of the real-time integrated collaboration of the different enterprise application systems. Manufacturing process planning plays a significant role by providing collaborative integration capabilities, from design to manufacturing. This situation is more acute in the tooling production industry, which is characterized by short lead-time and frequent dynamic customer requirements. A framework for concurrent design to manufacturing collaboration has been developed to support the integration of product design with manufacturing process planning. A prototype system based on this framework has been developed and tested in a tooling job shop with satisfactory results. Although the concurrent design to manufacturing collaboration framework has been developed for solving tooling production problems, it is generic and can be effectively applied in other production domains that require the support of collaborative integration.

Large engineered systems do not often live out their lifecycles as originally planned. Traditional design methods do not address redesign issues that arise during the operation of these systems. The problem of how to consider the environmental impacts of stranded assets is especially problematic. This paper presents a method for analysis of a dynamically changing system that includes consideration of both economic and environmental impacts. A case study of an electrical power system illustrates the approach. The results provide several insights that were gained through the ability to forecast the environmental impact caused by lifecycle changes of a system, such as early retirement or operational life extension of facilities.