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Industrial glass blowing is an essential stage of manufacturing glass containers, i.e., bottles or jars. An initial glass preform is brought into a mold and subsequently blown into the mold shape. Over the past few decades, a wide range of numerical models for forward glass blow process simulation has been developed. A considerable challenge is the inverse problem: to determine an optimal preform from the desired container shape. A simulation model for blowing glass containers based on finite element methods has previously been developed (Giannopapa, 2008 "Development of a Computer Simulation Model for Blowing Glass Containers," ASME J. Manuf Sci. Eng., 130, p. 041003; Giannopapa and Groot, 2007," A Computer Simulation Model for the Blow-Blow Forming Process of Glass Containers," 2007 ASME Pressure Vessels and Piping Conference and 8th International Conference on CREEP and Fatigue at Elevated Temperature). This model uses level set methods to track the glass-air interfaces. The model described in a previous paper of the authors showed how to pemform the forward computation of a final bottle from the given initial preform without using optimization. This paper introduces a method to opti nize the shape of the preform combined with the existing simulation model. In particulary the new optimization method presented aims at minimizing the error in the level set representing the glass-air interfaces of the desired container The number of parameters used for the optimization is restricted to a number of control points for describing the interfaces of the preform by parametric curves, from which the preform level set function can he reconstructed. Numerical applications used for the preform optimization method presented are the blowing of an axisymmetrical ellipsoidal container and an axisymmetrical jar. [ABSTRACT FROM AUTHOR]

A material's design revolution is underway with a focus to design the material microstructure and processing paths to achieve certain performance requirements of products. A host of manufacturing processes are involved in producing a product. The processing carried out in each process influences its final properties. To couple the material processing-structure-property-performance (PSPP) spaces, models of specific manufacturing processes must be enhanced and integrated using multiscale modeling techniques (vertical integration) and then the input and output of the various manufacturing processes must be integrated to facilitate the flow of information from one process to another (horizontal integration). Together vertical and horizontal integration allows for the decision-based design exploration of the manufacturing process chain in an inverse manner to realize the end product. In this paper, we present an inverse method to achieve the integrated design exploration of materials, products, and manufacturing processes through the vertical and horizontal integration of models. The method is supported by the concept exploration framework (CEF) to systematically explore design alternatives and generate satisficing design solutions. The efficacy of the method is illustrated for a hot rod rolling (HRR) and cooling process chain problem by exploring the processing paths and microstructure in an inverse manner to produce a rod with specific mechanical properties. The proposed method and the exploration framework are generic and support the integrated decision-based design exploration of a process chain to realize an end product by tailoring material microstructures and processing paths. [ABSTRACT FROM AUTHOR]

The accurate tracking of tool-paths on five-axis CNC machine tools is essential in achieving high speed machining of dies, molds, and aerospace parts with sculptured surfaces. Because traditional CNCs control the tracking errors of individual drives of the machine, this may not lead to desired contouring accuracy along tool-paths, which require coordinated action of all the five drives. This paper proposes a new control approach where the tool tip and tool orientation errors, i.e., the contouring errors, are minimized along the five-axis tool-paths. The contouring error and kinematic model of the machine, which are presented in Part I of the paper, are used in defining the plant. A multi-input-multi-output sliding mode controller which tries to minimize path tracking and path following velocity errors, is introduced. The stability of the system is ensured, and the proposed model is experimentally demonstrated on a five-axis machine tool. The path errors originating from the dynamics of five simultaneously active drives are significantly reduced. [ABSTRACT FROM AUTHOR]

Aerospace, die, and mold industries utilize parts with sculptured surfaces, which are machined on five-axis computer numerical controlled machine tools. Accurate path tracking for contouring is not always possible along the desired space curves due to the loss of joint coordination during the five-axis motion. This two-part paper presents modeling and robust control of contouring errors for five-axis machines. In Part I, two types of contouring errors are defined by considering the normal deviation of tool tip from the reference path, and by the normal deviation of the tool axis orientation from the reference orientation trajectory defined in the spherical coordinates. Overall contouring errors are modeled during five-axis motion that has simultaneous translation and rotary motions. The coupled kinematic configuration and the rigid body dynamics of all five drives are considered. The contouring error model is experimentally validated on a five-axis machine tool. The error model developed in this paper is then used for simultaneous, real- time robust control of all five drives in Part II. [ABSTRACT FROM AUTHOR]

The fault diagnosis plays an important role for product quality improvement in the multistation assembly processes (MAPs) and the efficiency of diagnosis significantly depends on the sensor distribution strategy, such as the number and location of the sensor The diagnosis-oriented sensor distribution optimization in MAP has been studied for the purpose of a full diagnosis of the process faults with the minimum sensing stations number as well as the minimum sensor number. However the existing studies are time consuming with the complex analysis and calculation processes, and no intuitive principles are given directly, according to the process configuration. In this paper a simplified method for the optimal sensor distribution is presented for a fully diagnosis of the process faults. First, two different types of assembly modes are defined and the variation trans-missibility ratios for these two assembly modes are discussed based on the process configuration. Then, the conditions for between-station diagnosability and within-station diagnosability are analyzed, respectively. Based on the results, the optimal sensor distribution method is derived finally. After comparing with the former methods, the optimal sensor distribution in this paper is based only on the process configuration without using for model-based matrix computation. Therefore, the proposed method greatly simplified the process. [ABSTRACT FROM AUTHOR]

In this paper, a novel modified scheme and effective computer representation for design of a plunge shaving cutter is presented. The paper aims to develop a novel design of shaving cutter for plunge shaving of precision involute gears. The study is carried out on the premise of satisfaction of the fifth necessary condition of proper part surface generation (PSG) when designing the plunge shaving cutter. In the current study, the author’s earlier developed DG/K method of surface generation is used together with the principal elements of analytical mechanics of gears. (The DG/K method is based on fundamental results obtained in differential geometry of surfaces, and on kinematics of multi-parametric motion of a rigid body in the E3 space. The interested reader may wish to go for details to the monograph: Radzevich, S.P., Fundamentals of Surface Generation, Monograph, Kiev, Rastan, 2001, 592 pp., and to: Radzevich, S.P., Sculptured Surface Machining on Multi-Axis NC Machine, Monograph, Kiev, Vishcha Schola, 1991, 192 pp.) In the particular case under consideration, the method employs (a) an analytical description of the gear tooth surface to be machined, (b) configuration of the plunge shaving cutter relative to the involute gear, (c) analytical representation of the coordinate systems transformations, and (d) the fifth condition of proper PSG that is adapted to finishing of precision involute gears. The fifth condition of proper PSG is investigated in the paper. On the premise of the obtained results of the investigation, a novel design of plunge shaving cutter for finishing of precision involute gears is proposed. The developed novel design of plunge shaving cutter can be used on shaving machines available on the market, e.g. on Gleason’s new Genesis™ 130SV computer numerical control (CNC) shaving machine. [ABSTRACT FROM AUTHOR]

This paper is aiming at development of an analytical approach for computation of the geometrical parameters of cutting edges of an involute hob. It is well recognized that the involute hob geometry strongly affects the cutting tool performance, as well as the efficiency of gear hobbing operation. It is proven experimentally and by industrial practice that the optimal value of every geometrical parameter of the tool cutting edge exists and, thus, it can be found out. A method for computation of the cutting edge geometry is necessary for optimization of parameters of a gear hobbing operation. In this paper; an analytical method for the computation of the cutting edge geometry of a gear hob is reported. The method is based on wide application of elements of vector calculus and matrices. The analysis is performed in the tool-in-use reference system. An equation of the penetration curve is derived. The machining zone is partitioned onto several different sectors. The roughing sector and the generating sector are distinguished. Generating of the work-gear tooth profile occurs within the generating sector that is bounded by the penetration curve. The derived equations, as well as the worked-out computer codes are applicable for computation of the cutting edge geometry at any point of the cutting edge of the hob, and at a any instant of time. The equations and the computer codes enable one estimating the impact of (a) the hob diameter; (b) the hob number of starts, (c) the work-gear number of teeth, (d) the hob feed rate, and (e) the hob rotation onto the actual values of the geometrical parameters of the hob cutting edges. Numerical results of the investigation are computed using commercial software MATHCAD-SCIENTIFIC. The results of the computation of the cutting edge geometry of the involute hob enable the user (a) to avoid not-feasible values of any and all geometrical parameters of the cutting edge of the hob teeth, (b) to develop parameters of the hob grinding and reliving operations, which guaranteed the optimal values of any and all geometrical parameters of the hob cutting edges. Ultimately, the application of the hobs with optimal geometry of the cutting edges will result in an increase in the cutting tool performance and in the efficiency of the gear hobbing operation. The latter is of critical importance for high volute production of involute gears for the needs of the automotive industry. The reported research results are ready to be put into practice. [ABSTRACT FROM AUTHOR]

This paper aims at development of a novel design of precision gear hob for machining involute gear on a conventional gear-hobbing machine. The reported research is based on use of fundamental results obtained in analytical mechanics of gearing. For solving the problem, both the descriptive-geometry-based (DGB) methods together with pure analytical methods have been employed. The use of DGB methods is insightful for solving most of the principal problems, which consequently were analytically solved. The analytical methods used provide an example of application of the DG/K-method of surface generation developed earlier by the author. For interpretation of the results of research, several computer codes in the commercial software MathCAD/Scientific were composed. Ultimately, a method of computation of parameters of design of a hob with straight-line lateral cutting edges for machining of precision involute gears is developed in the paper. Coincidence of the straight-line lateral cutting edges of the hob with the straight-line characteristics of it generating surface eliminates the major source of deviations of the hobbed involute gears. The relationships between major principal design parameters that affect the gear hob performance are investigated with the use of vector algebra, matrix calculus, and elements of differential geometry. Gear hobs of the proposed design yield elimination of the principal and major source of deviation of the desired hob tooth profile from the actual hob tooth profile. The reported results of this research are ready to put in practice. [ABSTRACT FROM AUTHOR]

In recent years the increased use of 3D scanning hardware has introduced a new type of data to the design and manufacturing field. in many design and manufacturing applications (e.g., part refurbishing or remanufacturing) a scanned 3D model may be provided as an input to a shape matching system to search the database for related or identical models with the purpose of extracting useful information. The introduction of scanned 3D models restricts the use of the CAD-based 3D model search and comparison methods' due to significant differences in model representations. The CAD models provide structured and high-level representation of the part features, whereas the scanned 3D models usually come in a polygonal mesh representation, which does not directly reveal engineering features of the part. These differences require new algorithms for comparing the shapes of scanned 3D models, ones that are robust against different scanning technologies and can be adjusted to work with different representations of the models. In this paper, a new approach and algorithms for scanned 3D shape matching and comparison are presented. Given the scanned 3D model as an input the approach first uses general-purpose shape matching methods to identify a small list of likely matches (i.e., candidate models) for more detailed shape comparison. To perform detailed comparison of the shapes each candidate model is geometrically adjusted (i.e., rotated and translated) with the input using one of two new viewpoint algorithms developed in this paper. Once the candidate models are adjusted they are compared to the input to identify the similarities and differences between their shapes. To accomplish this task a new 3D shape matching algorithm is developed. The relevance of the methodology developed in this paper is illustrated with the application of scanned 3D shape matching and comparison algorithms in rapid manufacturing of broken parts. [ABSTRACT FROM AUTHOR]

A reconfigurable manufacturing system (RMS) that is designed specifically to adapt to changes in production capacity, through system reconfiguration, is called a scalable-RMS. The set of system configurations that a scalable-RMS assumes as it changes over time is called its configuration path. This paper investigates how to determine the optimal configuration path of a scalable-RMS that minimizes investment and reconfiguration costs over a finite horizon with known demand. First, a practical cost model is presented to compute the reconfiguration cost between two scalable-RMS configurations. This model comprehends labor costs, lost capacity costs, and investment/salvage costs due to system reconfiguration and ramp up. Second, the paper presents an optimal solution model for the multiperiod scalable-RMS using dynamic programming (DP). Third, a combined integer programming/dynamic programming (IP-DP) heuristic is presented that allows the user to control the number of system configurations considered by the DP in order to reduce the solution time while still providing a reasonable solution. Numerical problems involving a two-stage and a three-stage scalable-RMS are solved using the DP and IP-DP methodologies. Experimental results suggest that the DP approach, although it is optimal, is not computationally efficient for large problem sizes. However, the combined IP-DP approach offers reasonable results with much less computational effort. [ABSTRACT FROM AUTHOR]

This paper investigates the manufacturability limits of fin aspect ratios within two-fluid counter-flow microchannel arrays based on the stress state between laminae during diffusion bonding. In prior papers, it has been shown that the diffusion bonding of two-fluid systems by microlamination can result in regions of the device that do not directly transmit bonding pressure and, consequently result in unbonded regions leading to device leakage. A finite element model is used to analyze the stress state between laminae during diffusion bonding. The stress state is used to determine the critical stress necessary for diffusion bonding to occur in areas not receiving direct bonding pressure. Model results are compared with experimental results over a wide range of counter-flow geometries. It has been found generally that a compressive stress state must exist in every part of the geometry in order to produce leak-free bonds. Implications of this funding on time design of two-fluid microchannel arrays are discussed. [ABSTRACT FROM AUTHOR]

Accurate process modeling requires the calculation of cutter/workpiece engagement (CWE) geometry. This is challenging when the geometry of the workpiece is changing unpredictably as is the case for most machined components of moderate complexity. Solid modelers are increasingly being considered as a computational engine for performing these calculations. This is largely due to increased robustness and computing efficiency that is evolving within this technology: The vast majority of reported research using solid modelers focuses on the domain of 2½ D machining with flat end mills. While significant there remain restrictions in the types of in-process workpiece geometry that can be processed with these approaches. In particular, they assume a constant axial engagement for a connected set of tool paths. This assumption cannot be made when the initial workpiece geometry is nonrectangular prismatic stock, when multiple setups are machined and when tool changes introduce tools of different diameters. In these cases the depth of engagement can vary over a single rotation of the cutter even though there is no axial feed motion. In this paper a solid modeling based solution is presented for calculating CWE geometry when multiple setups and tool changes are considered. Orthogonal setups and flat end mills are assumed so as to preclude cutter engagement on inclined workpiece faces. Intersections between a semi-cylinder representing the cutting tool and the workpiece are performed so as to generate the CWE geometry. Cutter Engagement Features (ceF) are used to characterize this geometry. Several classes of ceFs are defined to support this approach. The process of identifying ceFs is presented as a feature extraction problem. Algorithms for ceF extraction and parametrization are provided in this paper and validated using a test part. This is a new application for features which have traditionally been used to define final part geometry or in-process geometry between material removal steps. The results obtained validate the extraction algorithms presented. This work also extends the capabilities of solid modeling techniques for calculating CWE geometry. [ABSTRACT FROM AUTHOR]

Extensive research has been performed to investigate effective techniques, including advanced sensors and new monitoring methods, to develop reliable condition monitoring systems for industrial applications. One promising approach to develop effective monitoring methods is the application of time-frequency analysis techniques to extract the crucial characteristics of the sensor signals. This paper investigates the effectiveness of a new time-frequency analysis method based on Empirical Model Decomposition and Hilbert transform for analyzing the nonstationary cutting force signal of the machining process. The advantage of EMD is its ability to adaptively decompose an arbitrary complicated time series into a set of components, called intrinsic mode functions (IMFs), which has particular physical meaning. By decomposing the time series into IMFs, it is flexible to perform the Hilbert transform to calculate the instantaneous frequencies and to generate effective time-frequency distributions called Hilbert spectra. Two effective approaches have been proposed in this paper for the effective detection of tool breakage. One approach is to identify the tool breakage in the Hilbert spectrum, and the other is to detect the tool breakage by means of the energies of the characteristic IMFs associated with characteristic frequencies of the milling process. The effectiveness of the proposed methods has been demonstrated by considerable experimental results. Experimental results show that (1) the relative significance of the energies associated with the characteristic frequencies of milling process in the Hilbert spectra indicates effectively the occurrence of tool breakage; (2) the IMFs are able to adaptively separate the characteristic frequencies. When tool breakage occurs the energies of the associated characteristic IMFs change in opposite directions, which is different from the effect of changes of the cutting conditions e.g. the depth of cut and spindle speed. Consequently, the proposed approach is not only able to effectively capture the significant information reflecting the tool condition, but also reduces the sensitivity to the effect of various uncertainties, and thus has good potential for industrial applications. [ABSTRACT FROM AUTHOR]

Finish milling with a ball end mill is a key process in manufacturing high-precision and complex workpieces, such as dies and molds. Because of the complexity of the milling process, it is difficult to evaluate the microcharacteristics of machined surfaces real time, which necessitates the simulation of the process. In this area, the existing related simulation researches mainly focus on scallop height evaluation, but few have presented a whole picture of the microcharacteristics of milled surfaces. This paper develops a comprehensive simulation system based on a Z-map model for predicting surface topographic features and roughness formed in the finish milling process and studies the effect of machining parameters. The adoption of the discretization concept of the tool's cutting motion makes it possible to dynamically track the cutting tool-workpiece interaction with the tool movement and to describe the cutting edges-workpiece discrete cutting interaction more realistically and, therefore, the microcharacteristics of the machined surfaces more accurately. Also, the effects of the cutting tool run-out and wear are incorporated into the developed model through modifying the tool center motion and the cutting-edge shape, respectively. As a fundamental study, the tool-swept envelope has been simulated. The developed simulation system is applied to thoroughly study the surface features formed by the 2.5-axis finish milling process. The application for general three-axis machining is discussed. Additionally, this paper studies the effect of the tool inclination, which is the most common characteristic in 3+2- or five-axis milling processes, on the machined surface features. Experiments are carried out to study the milling process and to verify the simulation results. The difference between the simulated and experimental results is discussed, and the reason behind the difference is explored. [ABSTRACT FROM AUTHOR]

It is common for materials processing operations to have adjustable features that may be used to improve the quality of the final product when variability in operating conditions is encountered. This paper considers the polymer sheeting die design problem where variability in operating temperature or material properties, for example, requires that the die be designed to perform well under multiple operating conditions. An optimization procedure is presented where the design variables parametrize both stationary and adjustable model variables. In this approach, adjustable features of the die cavity are modified in an optimal manner consistent with the overall design objectives. The computational design approach incorporates finite element simulations based on the Generalized Hele-Shaw approximation to evaluate the die's performance measures, and includes a gradient-based optimization algorithm and analytical design sensitivities to update the die's geometry. Examples are provided to illustrate the design methodology where die cavities are designed to accommodate multiple materials, multiple flow rates, and various temperatures. This paper demonstrates that improved tooling designs may be computed with an optimization-based process design approach that incorporates the effect of adjustable features. [ABSTRACT FROM AUTHOR]

This paper presents a swept envelope approach to determining the optimal tool orientation for five-axis tool-end machining. The swept profile of the cutter is determined based on the tool motion. By analyzing the swept profile against the part geometry, four types of machining errors (local gouge, side gouge, rear gouge, and global collision) are identified. The tool orientation is then corrected to avoid such errors. The cutter's swept envelope is further constructed by integrating the intermediate swept profiles, and can be applied to NC simulation and verification. This paper analyzes the properties of the swept profile of a general cutter in five-axis tool-end machining. The relation of the swept profile, the part geometry, the tool motion, and the machining errors is developed. Therefore, the error sources can be detected early and prevented during tool path planning. The analytical results indicate that the optimal tool orientation occurs when the curvature of the cutter's swept profile matches with the curvature of the local part surface. In addition, the optimal cutting direction generally follows the minimum curvature direction. Computer illustrations and example demonstrations are shown in this paper. The results reveal the developed method can accurately determine the optimal tool orientation and efficiently avoid machining errors for five-axis tool-end machining. [ABSTRACT FROM AUTHOR]

In this paper, a permeability measurement method using hybrid fiber preforms is presented. The hybrid fiber preform can be composed of different fiber mat types, different numbers of fiber mats of the same type, or both. The computational procedure for permeability based on flow front location and flow time data was derived. This approach was validated by both simulation and experimental studies. The results show that by using this method, permeability values of different fiber mat types or the relationship between permeability and fiber volume fraction (porosity) can be obtained through a single experiment. This permeability measurement method based on hybrid fiber preforms yields compatible measurement accuracies while significantly improving the measurement efficiency. It provides a fast, accurate, and easy-to-use approach for permeability characterization, which is of great significance for the integrated composite product and process development. In this paper, a permeability measurement method using hybrid fiber preforms is presented. The hybrid fiber preform can be composed of different fiber mat types, different numbers of fiber mats of the same type, or both. The computational procedure for permeability based on flow front location and flow time data was derived. This approach was validated by both simulation and experimental studies. The results show that by using this method, permeability values of different fiber mat types or the relationship between permeability and fiber volume fraction (porosity) can be obtained through a single experiment. This permeability measurement method based on hybrid fiber preforms yields compatible measurement accuracies while significantly improving the measurement efficiency. It provides a fast, accurate, and easy-to-use approach for permeability characterization, which is of great significance for the integrated composite product and process development. [ABSTRACT FROM AUTHOR]

This paper presents a study on dimensional variations and tolerance analysis and synthesis for polymer matrix fiber-reinforced composite components and assemblies. A composite component dimensional variation model was developed with process simulation based on thermal stress analysis and finite element analysis (FEA ). Using the FEA-based dimensional variation model the deformations of typical composite structures were studied and the regression-based dimensional variation models were developed. The regression-based dimensional variation models can significantly reduce computation time and provide a quick design guide for composite products with reduced dimensional variations. By introducing a material modification coefficient, the comprehensive regression models can handle various fiber and resin types and stacking sequences, which eliminates the complicated, time-consuming finite element meshing and material parameter defining process. A structural tree method (STM) was developed for rapid computation of composite assembly dimensional variations resulting from deformations on individual components, as well as the deformation of composite components with complex shapes. With the STM and the regression-based dimensional variation models, rapid design optimization was conducted to reduce the dimensional variations of composite assemblies. Cost-tolerance functions were developed using a fuzzy multiattribute utility theory based cost-estimation method. Based on the developed dimensional variation and cost-tolerance models, composite assembly tolerance analysis and synthesis were performed in this study. The exploring research work presented in this paper provides a foundation for developing practical and productive dimensional control techniques for composite products. [ABSTRACT FROM AUTHOR]

Optimizing the milling process requires a priori knowledge of injury process variables. However, the ability to include both milling stability and accuracy information is limited because current methods do not provide simultaneous milling stability and accuracy predictions. The method described within this paper, called Temporal Finite Element Analysis (TFEA), provides an approach for simultaneous prediction of milling stability and surface location error. This paper details the application of this approach to a multiple mode system in two orthogonal directions. The TFEA method forms an approximate analytical solution by dividing the time in the cut into a finite number of elements. The approximate solution is then matched with the exact solution for free vibration to obtain a discrete linear map. The formulated dynamic map is then used u, determine stability steady-state surface location error, and to reconstruct the time series for a stable cutting process. Solution convergence is evaluated by simply increasing the number of elements and through comparisons with numerical integration. Analytical predictions are compared to several different milling experiments. An interesting period two behavior, which was originally believed to be a flip bifurcation, was observed during experiment. However, evidence is presented to show this behavior can be attributed to runout in the cutter teeth. [ABSTRACT FROM AUTHOR]

A transfer or progressive die process consists of multiple stations working simultaneously in each stroke. This paper aims to develop a new methodology that can decompose press tonnage signals to obtain individual station signals without using in-die sensors. In the paper, two different tonnage decomposition tests, as well as the associated data analysis algorithms, are developed. Statistical profile analyses and an in-die sensor test were conducted to validate the proposed methodology. [ABSTRACT FROM AUTHOR]

Quality control and metrology are critical to improved productivity and yield in MEMS design and production. This paper presents a micrograting interferometer for use in measuring MEMS devices, The sensor is also capable of making dynamic measurements, qualifying the functionality of the MEMS devices. The system employs a phase sensitive diffraction grating for interferometric axial resolution and a microfabricated lens for improved lateral resolution. The microinterferometer is capable of array implementation and can be used to increase the yield of MEMS manufacturing processes. The results generated by a single microinterferometer show good correlation with both analytic models and measurements of the MEMS devices by other metrology tools. The microinterferometer enables measurement of steady state vibration of MEMS devices as well as the development of surface vibration profiles. Initial results presented in this paper also demonstrate the ability to measure quantities such as part surface curvature, as well as reduce low frequency vibrational noise. The use of a deformable diffraction grating is proposed to further enhance the sensor's capabilities. [ABSTRACT FROM AUTHOR]

Optical fibers are drawn from preforms (fused silica glass rods) typically made up of two concentric cylinders (the core rod and the clad tube), which are usually joined in a separate fusion process. The setup time and hence manufacturing cost can be significantly reduced if the two cylinders can be joined in the same furnace in which the fiber is drawn. A good understanding of the transient temperature distribution is needed for controlling the feed rate to avoid thermally induced cracks. Since direct measurement of the temperature fields is often impossible, the geometrical design of the preform and the control of the feed rate have largely been accomplished by trials-and-errors. The ability to predict the transient temperature distribution and the thermally induced stresses will provide a rational basis to design optimization and feed rate control of the process. In this paper we present an analytical model to predict the transient conductive-radiative transfer as two partially joined, concentric glass cylinders with specular surfaces are fed into the furnace. Finite volume method (FVM) is used to solve the radiative transfer equation (RTE). The specular surface reflectivity is obtained by the Fresnel's law and the Snell's law. The boundary intensities are obtained through the coupling of the interior glass radiative transfer and the exterior furnace enclosure analysis. The model has been used to numerically study the transient conductive-radiative transfer in the advanced melting zone (AMZ) of an optic fiber drawing process. This problem is of both theoretical and practical interest in the manufacture of optical fibers. The computational method for the radiation transfer developed in this paper can also be applied to the simulation of the fiber drawing process and other glass-related manufacturing processes. [ABSTRACT FROM AUTHOR]

This paper discusses the development of an enhanced, static model of chip formation in micromilling processes that is able to describe the intermittency of the chip formation observed at low feeds per tooth due to the dominance of the minimum chip thickness effect Experimental analyses demonstrate the validity of the proposed model by verifying the level of periodicity in the cutting forces present at various feeds per tooth. A key finding of this study is the identification of a local maximum in the radial thrust forces in the micromilling process during the noncutting regime, at feeds per tooth that are of the order of the minimum chip thickness. To overcome the challenges in the direct measurement of the minimum chip thickness, this paper presents a method for estimating the minimum chip thickness of various combinations of tools and workpiece materials based on easily attainable cutting-force data. A discussion on the selection of process parameters to avoid intermittent chip formation is also presented. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive review of the literature, mostly of the last 10-15 years, that is enhancing our understanding of the mechanics of the rapidly growing field of micromachining. The paper focuses on the mechanics of the process, discussing both experimental and modeling studies, and includes some work that, while not directly focused on micromachining, provides important insights to the field. Experimental work includes the size effect and minimum chip thickness effect, elastic-plastic deformation, and micro structure effects in micromachining. Modeling studies include molecular dynamics methods, finite element methods, mechanistic modeling work, and the emerging field of multiscale modeling. Some comments on future needs and directions are also offered. [ABSTRACT FROM AUTHOR]

Finish milling is usually required in the peripheral milling of thin aircraft webs with long end mills, where the structures are flexible and radial depths of cut are small. The spindle speed and depth of cut must be selected optimally to avoid both forced and chatter vibrations, which in turn enables production of the parts within specified tolerances. Recent articles show that stability pockets differ at certain speeds when the radial immersion in milling is low and the machining process is highly intermittent. This paper presents a stability theory which predicts chatter stability lobes that are not covered by classical chatter theories in which the coupling between the spindle speed and process stability are neglected. The dynamics of low radial immersion milling are formulated as an eigenvalue problem, where harmonics of the tooth spacing angle and spread of the transfer function with the harmonics of the tooth passing frequencies are considered. It is shown that the stability lobes are accurately predicted with the presented method. This paper details the physics involved when the tooth passing frequencies alter the effective transfer function of the structure in the stability solution. The products of the harmonics of the directional coefficients and transfer functions of the structure are evaluated at the natural mode under the influence of tooth passing frequency harmonics in order to obtain the exact locations of chatter stability lobes. [ABSTRACT FROM AUTHOR]

In Part 1 of this paper a model was developed to describe the formation mechanisms and dynamic behavior of cutting fluid mist. This part of the paper focuses on an experimental investigation of the mist generated by the interaction of the fluid with the rotating cylindrical workpiece during a turning operation and the simulation of the dynamic behavior of the mist droplets, resulting in the prediction of the droplet size distribution and the mass concentration within the machining environment. These simulation results are compared to experimental measurements in order to validate the theoretical model presented in Part 1 of the paper It is observed that the model predictions accurately characterize the observed experimental behavior [ABSTRACT FROM AUTHOR]

Increasing attention is being devoted to the airborne emissions resulting from a variety of manufacturing processes because of health, safety, and environmental concerns. In this two-part paper, a model is presented for the amount of cutting fluid mist produced by the interaction of the fluid with the rotating cylindrical workpiece during a turning operation. This model is based on relationships that describe cutting fluid atomization, droplet settling, and droplet evaporation. Experiments are performed to validate the model. In Part 1 of the paper, the emphasis is on model development. In the model, thin film theory is used to determine the maximum fluid load that can be supported by a rotating cylindrical workpiece; rotating disk atomization theory is applied to the turning process to predict the mean size of the droplets generated by atomization; and expressions for both the evaporation and settling behavior are established. Droplet size distribution and mass concentration predictions are used to characterize the fluid mist. Model predictions indicate that the droplet mean diameter is affected by both fluid properties and operating conditions, with cutting speed having the most significant affect. Model predictions and experimental results show that the number distribution of droplets within the control volume is dominated by small droplets because of the settling and evaporation phenomena. In Part 2 of the paper, the cutting fluid mist behavior model is validated using the results obtained from a series of experiments. [ABSTRACT FROM AUTHOR]

A new approach for boundary conformed toolpath generation is presented in this paper. The approach combines the numerical Laplace solution for initial parametrization and a parametric redistribution algorithm for improved toolpath generation. The Laplace parametrization can be applied to any 2D surface domain without anomalies. Our parametric redistribution algorithm can then be used to reduce the unevenness that usually occurs in Laplace parametrization. The adequacy of computational robustness and efficiency of the parametric redistribution method are tested in this paper. By applying the parametric redistribution method, both the machining efficiency and uniformity of the resultant toolpaths can be improved. The advantages of this boundary conformed toolpath generation approach are successfully demonstrated on several typical examples. [ABSTRACT FROM AUTHOR]

This is the second of two papers concerned with on-line optimization of cylindrical plunge grinding cycles with continuously varying infeed control. In the first paper [1], dynamic programming was applied to a simulation of the cylindrical grinding process in order to explore the characteristics of optimal grinding cycles. Optimal cycles were found to consist of distinct segments each with predominant constraints. An optimal control policy was formulated with the infeed rate within each segment determined according to the prevailing constraint. The present paper is concerned with the design of the controller and its implementation. The control system to implement the optimization policy is described together with provisions to enhance robustness to modeling uncertainty and measurement noise. Robustness provisions include model adaptation by parameter estimation from on-line measurements of size and power, and incorporation of safety margins in the optimization process. Problems associated with practical implementation of the control system, stemming from power limitations and wheel wear, are also discussed. The controller performance is demonstrated on an instrumented internal cylindrical grinding machine. [ABSTRACT FROM AUTHOR]

A new methodology is developed for optimal infeed control of cylindrical plunge grinding cycles. Unlike conventional cycles having a few sequential stages with discrete infeed rates, the new methodology allows for continuous variation of the infeed rate to further reduce the cycle time. Distinctive characteristics of optimal grinding cycles with variable infeed rates were investigated by applying dynamic programming to a simulation of the grinding cycle. The simulated optimal cycles were found to consist of distinct segments with predominant constraints. This provided the basis for an optimal control policy whereby the infeed rate is determined according to the active constraint at each segment of the cycle. Accordingly, the controller is designed to identify the state of the cycle at each sampling instant from on-line measurements of power and size, and to then compute the infeed rate according to the optimal policy associated with that state. The optimization policy is described in this paper, and the controller design and its implementation are presented in the following paper [1]. [ABSTRACT FROM AUTHOR]

Process Integration has been applied in several industrial processes mainly using standard shell and tube heat exchangers (1-1 or 1-2). The flow arrangement in 1-2 multiple shell and tube heat exchangers involves part counter-current flow and part co-current flow. This fact is accounted for in the design by introducing a FT correction factor into the 1-1 heat exchanger design equation. To avoid some steep regions in the feasible space of heat exchangers design some authors introduce other parameters like Xp or G. Until now it was not possible to have an overall map to give some guidelines of how to choose between the several Xp approaches established in the literature. This paper summarizes the current existing criteria in a general design algorithm (DeAl12) to show a path for the calculations of the main design variables of the heat exchanger Also a new strategy design algorithm (StratDeAl12) is introduced in this paper to allow the best choice between the existing Xp approaches based on the heat exchanger cost minimisation. Several examples illustrate the advantage of using the developed algorithm and the deviations obtained in the heat exchanger cost if a wrong approach was chosen. [ABSTRACT FROM AUTHOR]

This paper presents a method of diagnosing variance components of process error sources in singular manufacturing systems. The singularity problem is studied and the cause examined in the context of fixture error diagnosis in multi-station assembly processes. The singularity problem results in nondiagnosable fixture errors when standard least-squares (LS) estimation methods are used. This paper suggests a reformulation of the original error propagation model into a covariance relation. The LS criterion is then applied directly to the sample covariance matrix to estimate the variance components. Diagnosability conditions for this variance LS estimator are derived, and it is demonstrated that certain singular systems that are not diagnosable using traditional LS methods become diagnosable with the variance LS estimator Modified versions that improve the accuracy of the variance LS estimator are also presented. The various procedures are thoroughly contrasted, in terms of accuracy and diagnosability. The results are illustrated with examples from panel assembly, although the application of the approach and the conclusions extend to more general distrete-part manufacturing processes where fixtures are used to ensure dimensional accuracy of the final product. [ABSTRACT FROM AUTHOR]

Deterministic micro asperities show potential for enhancement of lubrication in conformal contacts as found in many bearing and seal designs. Several manufacturing methods have been proposed for deterministic micro asperities. Of these, laser texturing has emerged as the most viable option. This paper proposes the LIGA MEMs manufacturing method as an alternative. Using LIGA, surfaces with patterned micron sized surface features of arbitrary cross section (cylindrical, hex, triangular, etc.) can be fabricated from electroplated nickel gel-cast silicon nitride, or plastic. The resulting asperities can be positive (protuberances) or negative (recesses) and can have heights (depths) from 1-1000 microns and be patterned over surface areas up to about 150 mm x 150 mm. In this paper, the LIGA method is used to fabricate a sample thrust bearing surface with a hexagonal array of positive asperities. The resulting asperities are 550 µm in average diameter, 165 µm in edge-to-edge spacing and have heights of 3-100 µm. Surface metrology indicates submicron accuracy of form and 13 nm Ra roughness on the asperity tops (land). Tribology testing in a nonpressurized oil bath indicates full film conditions and shows a 14-22% reduction in friction coefficient for a thrust surface covered with the micro asperities. A model confirms the experimental trends and indicates the potential to further reduce the friction coefficient by about 60% through optimization of the asperity geometry and layout. [ABSTRACT FROM AUTHOR]

Sheet metal forming is one of the most important and frequently used manufacturing processes in industry today. One of the key parameters affecting the forming process is the blank holder force (BHF). In the past, researchers have demonstrated the advantages of varying the blank holder force during the forming process, that is, the two primary modes of failure in sheet metal forming (wrinkling and tearing) are avoided. This gives rise to improved formability, higher accuracy and better part consistency. In recent years, researchers have also shown increasing interest in forming processes where the blank holder force is varied spatially with the help of segmented binders or flexible binders. In this paper, we have combined the above two aspects and used a robust method to determine the blank holder force trajectories for a non-circular part using segmented binders. The proposed strategy is verified by implementing it into a finite element simulation. Binder force is treated as a system input. The displacement of the binder is used as a measure of the tendency to wrinkle, and is therefore treated as a system output. The parameters of the system are continuously identified and updated using a deterministic Auto-Regressive Moving-Average model (ARMA). The model is then used to control the binder displacement to a prescribed value by adjusting the system input, i.e., the binder force. In this manner, individual binder force profiles for each of the segmented binders are obtained. Due to the generic nature of the ARMA model, the strategy proposed in this paper can be applied to a variety of forming problems, making it a robust approach. [ABSTRACT FROM AUTHOR]

In this paper, we present a method to determine the capability envelope of a machining process which consists of a sequence of parameterized machining operations. First, operations as well as workpiece in a machining process are represented using a Parametric Feature Relational Graph (P-FRG). Second, the workpiece P-FRG within a process is updated step-by-step by mixing with operation P-FRGs as the operations in the process are successively applied to it. Since alternative setups may exist for an operation, a tree of workpiece P-FRGs can be generated for a process. All the P-FRGs at the leaf nodes of the tree together form the capability envelope of the machining process, that is, the envelope of the parts that can be produced using the process from a given initial workpiece. The parameter mappings, from the parameters of a machining process to the parameters of a part P-FRG in the capability envelope, are also given in this paper The capability envelope can be applied to the integration of part design and process planning. [ABSTRACT FROM AUTHOR]

Workpiece localization has direct relations with many manufacturing automation applications. In order to gain accurate workpiece measurement by on-machine measurement system or coordinate measuring machines (CMM), the touch trigger probe is widely adopted. In spite of the high repeatability of the touch trigger probe, there are still error sources associated with the probe. In this paper, we will focus on probe radius compensation. We first show the sources of probe radius error. Then, several compensation methods in related papers are reviewed. After that, a new radius compensation method is proposed in this paper. Simulation and experimental results of probe radius compensation by different methods are given. It is shown that our proposed method has the best performance both in terms of compensation accuracy and computational time. The method is also implemented in a computer aided setup (CAS) system. [ABSTRACT FROM AUTHOR]

Selective assembly is a means of obtaining higher quality product assemblies by using relatively low-quality components. Components are selected and classified according to their dimensions and then assembled. Past research has often focused on components that have normal dimensional distributions to try to find assemblies with minimal variation and surplus parts. This paper presents a multistage approach to selective assembly for all distributions of components and with no surplus, thus offering less variation compared to similar approaches. The problem is divided into different stages and a genetic algorithm (GA) is used to find the best combination of groups of parts in each stage. This approach is applied to two available cases from the literature. The results show improvement of up to 20% in variation compared to past approaches. [ABSTRACT FROM AUTHOR]

Dramatic advancements and adoption of computing capabilities, communication technologies, and advanced, pervasive sensing have impacted every aspect of modern manufacturing. Furthermore, as society explores the Fourth Industrial Revolution characterized by access to and leveraging of knowledge in the manufacturing enterprise, the very character of manufacturing is rapidly evolving, with new, more complex processes, and radically, new products appearing in both the industries and academe. As for traditional manufacturing processes, they are also undergoing transformations in the sense that they face ever-increasing requirements in terms of quality, reliability, and productivity, needs that are being addressed in the knowledge domain. Finally, across all manufacturing we see the need to understand and control interactions between various stages of any given process, as well as interactions between multiple products produced in a manufacturing system. All these factors have motivated tremendous advancements in methodologies and applications of control theory in all aspects of manufacturing: at process and equipment level, manufacturing systems level, and operations level. Motivated by these factors, the purpose of this paper is to give a high-level overview of latest progress in process and operations control in modern manufacturing. Such a review of relevant work at various scales of manufacturing is aimed not only to offer interested readers information about state-of-the art in control methods and applications in manufacturing, but also to give researchers and practitioners a vision about where the direction of future research may be, especially in light of opportunities that lay as one concurrently looks at the process, system and operation levels of manufacturing. [ABSTRACT FROM AUTHOR]

Manufacturers consume about 27% of the total electricity in the U.S. and are among the main contributors in the rising electricity demand. End-user electricity demand response is an effective demand side management tool that can help energy suppliers reduce electricity generation expenditures while providing opportunities for manufacturers to decrease operating costs. Several studies on demand response for manufacturers have been conducted. However, there lacks a unified production model that balances production capability degradation, maintenance requirements, and time-of-use (TOU) electricity prices simultaneously such that the interaction between production, maintenance, and electricity costs is considered. In this paper, a cost-effective production and maintenance scheduling model considering TOU electricity demand response is presented. Additionally, an aggregate cost model is formulated, which considers production, maintenance, and demand response parameters in the same function. The proposed models provide manufacturers with tools for implementing feasible and cost-effective demand response while meeting production targets and efficiently allocating maintenance resources. A case study is performed and illustrates that 19% in cost savings can be achieved when using the proposed model compared to solely minimizing the electricity billing cost. In addition, 14% in cost savings can be achieved when using the proposed model compared to a strategy where only the maintenance cost is minimized. Finally, the benefits of demand response driven production and maintenance scheduling under different cost and parameter settings are investigated; where the rated power, production rate, and initial machine production capability show to have the largest impact on the cost effectiveness of implementing demand response. [ABSTRACT FROM AUTHOR]

High-resolution spatial data are essential for characterizing and monitoring surface quality in manufacturing. However, the measurement of high-resolution spatial data is generally expensive and time-consuming. Interpolation based on spatial models is a typical approach to cost-effectively acquire high-resolution data. Conventional modeling methods fail to adequately model the spatial correlation induced by periodicity, and thus their interpolation precision is limited. In this paper, we propose using a Bessel additive periodic variogram model to capture such spatial correlation. When combined with kriging, a geostatistical interpolation method, accurate interpolation performance can be achieved for common periodic surfaces. In addition, parameters of the proposed model provide valuable insights for the characterization and monitoring of spatial processes in manufacturing. Both simulated and real-world case studies are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Part consolidation (PC) is one of the typical design freedoms enabled by additive manufacturing (AM) processes. However, how to select potential candidates for PC is rarely discussed. This deficiency has hindered AM from wider applications in industry. Currently available design guidelines are based on obsolete heuristic rules provided for conventional manufacturing processes. This paper first revises these rules to take account of AM constraints and lifecycle factors so that efforts can be saved and used at the downstream detailed design stage. To automate the implementation of these revised rules, a numerical approach named PC candidate detection (PCCD) framework is proposed. This framework is comprised of two steps: construct functional and physical interaction (FPI) network and PCCD algorithm. FPI network is to abstractly represent the interaction relations between components as a graph whose nodes and edges have defined physical attributes. These attributes are taken as inputs for the PCCD algorithm to verify conformance to the revised rules. In this PCCD algorithm, verification sequence of rules, conflict handling, and the optimum grouping approach with the minimum part count are studied. Compared to manual ad hoc design practices, the proposed PCCD method shows promise in repeatability, retrievability, and efficiency. Two case studies of a throttle pedal and a tripod are presented to show the application and effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Roller infusion by nip rollers is widely used in the infusion industry with broad applications, which is also adopted as one of the seven steps of a newly developed manufacturing process for making fungal mycelium-based biocomposites. One important technical issue related to infusion textile reinforcements for such biocomposites is how to predict and control the infusion fluid penetration depth, which directly affects the quality and performances of the preformed textile skins. Currently, the analytical relations between the modeling parameters and the final infusion penetration depth are still not well understood. Few studies have been performed on such topic and some of which used oversimplified assumptions. A new analytical model is developed in this paper, and the infusion penetration curves are plotted based on certain input parameters including infusion speed, infusion fluid flow rate, and clamping forces of the two rollers. The model-calculated results are then validated by experiments that are performed with the same parameters. The measured parameters of prepared non-Newtonian starch-based natural glue are used both in the modeling and experiments, and the results are close enough for model validation. [ABSTRACT FROM AUTHOR]

Three-phase induction motors (TIMs) are present in most industrial processes, accounting for more than 60% of the energy consumption in industry. Despite their importance in the productive sector, few motors are properly monitored, mainly due to the high cost of the monitoring equipment and the invasiveness in their installation. This paper presents the implementation and deployment of an industrial wireless sensor network (WSN) to monitor three-phase induction motors. Embedded systems were developed to acquire signals of current and voltage from sensors installed in the motors' terminals, perform local processing to estimate torque and efficiency, and transmit the information through the WSN. The method used to estimate the variables is based on the air-gap torque method. Before the deployment in the industry, experiments were performed to validate the system in laboratory. Finally, the system was employed in a real industrial environment, where different analyses and diagnosis of three motors running were performed. Using the proposed system, the efficiency versus load curves of the motors could be obtained continuously, and an energy loss analysis due to the oversizing of the motors was performed. [ABSTRACT FROM AUTHOR]

This paper presents new techniques to analyze and understand the sensorimotor characteristics of manual operations such as grinding, and links their influence on process performance. A grinding task, though simple, requires the practitioner to combine elements from the large repertoire of his or her skillset. Based on the joint gaze, force, and velocity data collected from a series of manual grinding experiments, we have compared operators with different levels of experience and quantitatively described characteristics of human manual skill and their effects on manufacturing process parameters such as cutting energy, surface finish, and material removal rate (MRR). For instance, we find that an experienced subject performs the task in a precise manner by moving the tool in complex paths, with lower applied forces and velocities, and short fixations compared to a novice. A detailed understanding of gaze-motor behavior broadens our knowledge of how a manual task is executed. Our results help to provide this extra insight, and impact future efforts in workforce training as well as the digitalization of manual expertise, thereby facilitating the transformation of raw data into product-specific knowledge. [ABSTRACT FROM AUTHOR]

Discussion of big data (BD) has been about data, software, and methods with an emphasis on retail and personalization of services and products. Big data also has impacted engineering and manufacturing and has resulted in better and more efficient manufacturing operations, improved quality, and more personalized products. A less apparent effect is that big data have changed problem solving: the problems we choose to solve, the strategy we seek, and the tools we employ. This paper illustrates this point by showing how the big data style of thinking enabled the development of a new quality assurance philosophy called process monitoring for quality (PMQ). PMQ is a blend of process monitoring and quality control (QC) that is founded on big data and big model (BDBM), which are catalysts for the next step in the evolution of the quality movement. Process monitoring (PM) for quality was used to evaluate the performance of the ultrasonically welded battery tabs in the new Chevrolet Volt, an extended range electric vehicle. [ABSTRACT FROM AUTHOR]

Multisensor data fusion can enable comprehensive representation of manufacturing processes, thereby contributing to improved part quality control. The effectiveness of data fusion depends on the nature of the input data. This paper investigates orthogonality as a measure for the effectiveness of data fusion, with the goal to maximize data correlation with part quality toward manufacturing process control. By decomposing sensor data into a lifted-dimensional space, contribution from each of the sensors for quantifying part quality is revealed by the corresponding projection vector. Performance evaluation using data measured from polymer injection molding confirmed the effectiveness of the developed technique. [ABSTRACT FROM AUTHOR]

The packaging of electronic and microelectromechanical systems (MEMS) devices is an important part of the overall manufacturing process as it ensures mechanical robustness as well as required electrical/electromechanical functionalities. The packaging integration process involves the selection of packaging materials and technology, process design, fabrication, and testing. As the demand of functionalities of an electronic or MEMS device is increasing every passing year, chip size is getting larger and is occupying the majority of space within a package. This requires innovative packaging technologies so that integration can be done with less thermal/mechanical effect on the nearby components. Laser processing technologies for electronic and MEMS packaging have potential to obviate some of the difficulties associated with traditional packaging technologies and can become an attractive alternative for small-scale integration of components. As laser processing involves very fast localized and heating and cooling, the laser can be focused at micrometer scale to perform various packaging processes such as dicing, joining, and patterning at the microscale with minimal or no thermal effect on surrounding material or structure. As such, various laser processing technologies are currently being explored by researchers and also being utilized by electronic and MEMS packaging industries. This paper reviews the current and future trend of electronic and MEMS packaging and their manufacturing processes. Emphasis is given to the laser processing techniques that have the potential to revolutionize the future manufacturing of electronic and MEMS packages. [ABSTRACT FROM AUTHOR]

Modern cyber-physical production systems (CPPS) connect different elements like machine tools and workpieces. The constituent elements are often equipped with high-performance sensors as well as information and communication technology, enabling them to interact with each other. This leads to an increasing amount and complexity of data that requires better analysis tools to support system refinement and revision performed by an expert. This paper presents a user-guided visual analysis approach that can answer relevant questions concerning the behavior of cyber-physical systems. The approach generates visualizations of aggregated views that capture an entire production system as well as specific characteristics of individual data features. To show the applicability of the presented methodologies, an exemplary production system is simulated and analyzed. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) for mechanical devices and electronic components has been actively researched recently. While manufacturing of those mechanical and electronic devices has their own merits, combining them into a single form is expected to grow by creating new applications in the future. The so-called all-printed electromechanical devices have potential applications in mechanical, electrical, and biomedical engineering. In this paper, the recent advancement in all-printed electromechanical devices is reviewed. A brief introduction to various AM techniques is presented first. Then, various examples of sensors, electronics, and electromechanical devices created by AM are reviewed. [ABSTRACT FROM AUTHOR]

A key element for achieving sustainable manufacturing systems is efficient and effective resource use. This potentially can be achieved by encouraging symbiotic thinking among multiple manufacturers and industrial actors and establish resource flow structures that are analogous to material flows in natural ecosystems. In this paper, ecological principles used by ecologists for understanding food web (FW) structures are discussed which can provide new insight for improving closed-loop manufacturing networks. Quantitative ecological metrics for measuring the performance of natural ecosystems are employed. Specifically, cyclicity, which is used by ecologists to measure the presence and strength of the internal cycling of materials and energy in a system, is discussed. To test applicability, groupings of symbiotic eco-industrial parks (EIP) were made in terms of the level of internal cycling in the network structure (high, medium, basic, and none) based on the metric cyclicity. None of the industrial systems analyzed matched the average values and amounts of cycling seen in biological ecosystems. Having detritus actors, i.e., active recyclers, is a key element for achieving more complex cycling behavior. Higher cyclicity values also correspond to higher amounts of indirect cycling and pathway proliferation rate, i.e., the rate that the number of paths increases as path length increases. In FWs, when significant cycling is present, indirect flows dominate direct flows. The application of these principles has the potential for novel insights in the context of closed-loop manufacturing systems and sustainable manufacturing. [ABSTRACT FROM AUTHOR]