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The purpose of this paper is to investigate the effects of aging, pre‐conditioning, and build orientation on the mechanical properties of test samples fabricated using stereolithography (SL) and a commercially available resin.

American Society for Testing and Materials (ASTM) Standard D638 Type I specimens were manufactured in a Viper si2 SL system using WaterShed™ 11120 resin. The specimens were manufactured in two different build setups, designed to fit batches of 18 or 24 specimens with different build orientations. The specimens were randomly tested in tension, and a design of experiments (DOE) was used to determine the effect of aging (4, 30 or 120 days), pre‐conditioning (ambient, desiccant, or ASTM recommended conditioning), and build orientation (flat, on an edge, or vertical) on the ultimate tensile stress (UTS) and elastic modulus (E) of SL fabricated samples. Additionally, the fractured samples were imaged using scanning electron microscopy (SEM) to characterize the fractured surfaces.

Results showed that aging, pre‐conditioning, and build orientation each had an effect on the mechanical properties of the SL samples. In general, the samples aged at the shortest time frame (4 days) and the samples preconditioned according to ASTM recommendations had the lowest values of UTS. Regarding the effect of build orientation, the specimens built flat (with layers oriented along the thickness of the sample) had the lowest UTS and E values and the mechanical properties were statistically different from those built vertically or on an edge. The specimens built in the vertical orientation (with layers oriented along the length of the sample) had the highest values of UTS and E, yet the mechanical properties of the samples built on an edge (with layers oriented along the width of the sample) were not statistically different from the samples built vertically. SEM images of the fractured specimens showed fracture surfaces typical of polymers with a mirror zone and changes in surface texture from smooth to coarse.

The research was limited to a single commercially available resin. Through a statistical DOE approach, statistically significant differences in mechanical properties of SL fabricated samples were found as functions of aging, pre‐conditioning, and build orientation. These results can assist the ASTM F42 Committee with developing test standards specific to SL and the additive manufacturing community.

The statistical analyses presented here can help identify and classify the effects of fabrication, storage, and conditioning parameters on mechanical properties for SL fabricated parts. Understanding how the mechanical properties of SL resins are affected by different parameters can help improve the use of SL for a variety of applications including direct manufacturing of end‐use products.

Demand forecasting has long been an imperative tenet in production planning especially in a make-to-order environment where a typical manufacturer has to balance the issues of holding excessive safety stocks and experiencing possible stockout. Many studies provide pragmatic paradigms to generate demand forecasts (mainly based on smoothing forecasting models.) At the same time, artificial neural networks (ANNs) have been emerging as alternatives. In this chapter, we propose a two-stage forecasting approach, which combines the strengths of a neural network with a more conventional exponential smoothing model. In the first stage of this approach, a smoothing model estimates the series of demand forecasts. In the second stage, general regression neural network (GRNN) is applied to learn and then correct the errors of estimates. Our empirical study evaluates the use of different static and dynamic smoothing models and calibrates their synergies with GRNN. Various statistical tests are performed to compare the performances of the two-stage models (with error correction by neural network) and those of the original single-stage models (without error-correction by neural network). Comparisons with the single-stage GRNN are also included. Statistical results show that neural network correction leads to improvements to the forecasts made by all examined smoothing models and can outperform the single-stage GRNN in most cases. Relative performances at different levels of demand lumpiness are also examined.

The purpose of this paper is to identify, study and quantify the effects of lighting on yield and productivity in manual electronics assembly (MEA) and inspection as a limiting work design criterion. The study also examines the potential interactions among lighting option, workers' age, and years of experience.

A three‐factor full factorial experiment is adopted to statistically evaluate the independent variables (process yield and assembly time) versus randomly selected levels of three factors: type of light (low pressure sodium, mercury vapor lamps, and metal halide lamps measured in foot‐candle luminaries), operator age, and years on the job. A residual analysis is also conducted to complement and corroborate the ANOVA findings.

The study finds that metal halide lamps, based on the ANSI recommended ranges of 186‐464 foot‐candles, lead to significant increases in labor productivity and through‐put, irrespective of operators' age and years of experience. Although these lamps have a significantly shorter life span than that of low‐pressure sodium and mercury vapor lamps, the realized benefits far exceed the incremental cost of illumination devices. The results indicate that a modest capital investment is able to generate solid improvements in yield and processing time in a typical MEA environment.

The relations between productivity and lighting intensity and type have never been studied in the area of MEA. This empirical study uncovers the effects through a systematic experimentation of this essential relationship in a typical MEA environment. The findings, which can be generalized to other facilities, are validated by an array of statistical procedures and proved to be significant. The paper contributes useful knowledge to the fields of engineering management and facility design.

The primary purpose of this study is to illustrate a practical approach for industrial work process design that, in an integrative manner, captures essential concerns from different parties associated with manufacturing. It aims explicitly to incorporate utility expectation from the perspectives of operational managers, floor workers, and financial planners into the decision making process.

Through a real industrial scenario, the case study illustrates the use of a Bayesian belief network (BBN)‐based expert system and influence diagram in work process design. What‐if analysis is performed. Statistical tests are then used to benchmark and validate the experimental results and actual data.

The results suggest that the proposed BBN framework is effective in modeling and solving the work design problem. The findings can draw meaningful insights into the adoption and capacity of BBN in the fields of ergonomics, worker health management, and performance improvement.

Practically, the industrial problem is to compare the new stand‐up sewing cells against the traditional sit‐down sewing layout while taking into consideration of ergonomic effect (repetitive motion injury (RMI) likelihood), floor space (SF), yield (%), and cost ($). The study illustrates the use of an expert system and influence diagram to evaluate different alternatives for ergonomic work design in production process.

The results of this study can potentially improve health safety management and worker ergonomics.

The paper is among the few systematic studies that have applied BBN and influence diagram to production ergonomics and worker health management. A methodological framework utilizing these probabilistic reasoning techniques are developed. This new framework can capture essential concerns from different parties in manufacturing.

An analysis of the US border manufacturing industry revealed that, while a plentiful supply of inexpensive labor is available, there are high levels of absenteeism and turnover. This in turn has affected this industry’s ability to implement lean and agile manufacturing production environments. It was argued that lower inventory levels and quicker response time to market fluctuations are required for these manufacturers to stay competitive. Yet, without careful consideration of the idiosyncrasies of the infrastructure, the change to leaner and more agile manufacturing could destroy some of these plants. The high levels of absenteeism and turnover, which have a direct bearing on the low and variable product yield rates, could cause an agile and lean production system to fail. Yet this research has shown that a recursive, pull‐type production control system that will meet the required daily quota and minimize inventory while accounting for high levels of absenteeism and turnover that directly affect workstation yield rates would be advantageous. That is, a US border manufacturer can become leaner and more agile in spite of the drawbacks that are germane to the US border manufacturing industry.

This research provides an ergonomic analysis of the bucket brigade production line and identifies the potential ergonomic risk factors that may result from the utilization of this production technique. Biomechanical and physiological data of the workers was collected while they worked on the traditional and bucket brigade production lines. The research identifies that while the production level of the bucket brigade system may be higher than the traditional production line, its procedure required significantly less energy expenditure by the operators. However, the difficulty and amount of work experienced by the last worker in the bucket brigade line may cause productivity problems and promote a high turnover rate at that station, and thus is the limiting design criterion of the bucket brigade production methodology from a human factors perspective.

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Increasing competition within the global supply chain network has been pressuring managers to improve efficiencies of production systems while, at the same time, reduce manufacturing operation expenses. One well-known approach is to have better control of the manufacturing system through more accurate forecasting and efficient control. In other words, a production control paradigm with more reliable forward visibility should help in maintaining a cost-effective yet lean manufacturing environment. Hence, this study proposes a predictive decision support system for controlling and managing complex production environments and demonstrates a Visual Interactive Simulation (VIS) framework for forecasting system performances given a designated set of production control parameters. The VIS framework is applied to a real-world manufacturing system in which the primary objective is to minimize total production while maintaining consistently high throughput and controlling work-in-process level. Through this case study, we demonstrate the use and validate the effectiveness of VIS in optimization and prediction of the examined production system. Results show that the predictive VIS framework leads to better and more reliable decision making on selection of control parameters for the manufacturing system under study. Statistical analyses are incorporated to further strengthen the VIS decision-making process.

There has been extensive research on techniques to assign mechanics to machines in order to maximize their availability in corrective maintenance systems. However, the focus has been on achieving high machine availability, while disregarding the utilization of mechanics. The maintenance brigade system (MBS), a team‐based mechanic‐assignment technique based on the relay‐type, self‐balancing bucket brigade system created by Bartholdi and Eisenstein, was thus developed and tested. The MBS was compared to a traditional assignment technique via machine availability and mechanic utilization, each at different levels according to the industrial partner’s opinion of high and low, with medium levels taken to be the status quo. Each system was modeled and, after a validation and verification process, simulated under the same number of machines and mechanics. Results and implications are discussed

The objective of this paper is to demonstrate a method for producing embedded horizontal micro‐channels using a commercial line‐scan stereolithography (SL) system. To demonstrate that the method is repeatable, reproducible and capable of producing accurate horizontal micro‐channels, a statistical design of experiments was performed.

Demonstration of the technique was performed using a 3D Systems Viper si2^TM SL system and DSM Somos^® WaterShed^TM resin with polytetrafluoroethylene (PTFE)‐coated wire having diameters of 31.6 and 57.2 μm. By embedding the wire and building around the insert, the down‐facing surfaces were supported during fabrication enabling accurate fabrication of embedded micro‐channel geometries. The fabrication method involved first building an open micro‐channel, interrupting the SL process and inserting the wire, and then capping over the wire with multiple layers. After fabrication, the part with the inserted micro‐wire was post‐cured to harden any uncured resin around the wire. The micro‐channel was produced by simply pulling the wire out of the part. Scanning electron microscope images were used to examine and measure the geometries of the fabricated micro‐channels, and characterization through a statistical analysis was accomplished to show that the process was capable of producing accurate horizontal micro‐channels.

The measured data showed that the micro‐wires were successfully removed from the channels, leaving high quality micro‐channels, where the mean measured diameters for each wire were 2.65 and 2.18 μm smaller than the measured wire diameters (31.6 and 57.2 μm). Based on the statistical results, it is suggested that the method described in this work can rapidly produce repeatable and reproducible circular, embedded, and accurate micro‐channels.

The method developed in the current work was demonstrated on simple straight channels and a statistical study was used to show that the process is capable of repeatedly and reproducibly producing accurate micro‐channels with circular cross‐section; however, future studies are required to extend these procedures to more realistic and complicated geometries that may include non‐straight channel paths and non‐circular cross‐sectional geometries. The process can be used for micro‐channel fabrication with not only circular cross‐sectional geometries as shown here but potentially with a wide range of additional cross‐sectional geometries that can be fabricated into a PTFE‐coated micro‐wire.

This work demonstrates a process using commercial line‐scan SL and embedding a PTFE‐coated micro‐wire that is subsequently removed for producing repeatable and reproducible horizontal embedded micro‐channels of circular cross‐sectional geometries.