Rolando Quintana

Effects of environmental conditions, aging, and build orientations on the mechanical properties of ASTM type I specimens manufactured via stereolithography

Purpose – 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.Design/methodology/approach – 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 charac...

A production methodology for agile manufacturing in a high turnover environment

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.

Recursive linear control of order release to manufacturing cells with random yield

One-piece flow job shop production environments in high labor turnover environments are oftentimes characterized by late shipments and incomplete orders due to random and variable yield. The problem addressed in this paper is that of determining an order release policy for a one-piece flow prototype production line in order to meet demand in an environment subject to random and variable yield induced by high labor turnover. This paper is motivated by a problem encountered in a facility that produces prototype parts. The problem at hand can be defined as that of determining a lot size to release into the line to minimize deviations from the demand (i.e., target batch quota) for single-piece flow production in an environment characterized by random and variable yield. The objective of this research was to investigate the utility of recursive linear control as a mechanism for releasing parts into a single-piece flow production cell, and to develop a control algorithm using a Kalman filter. The methodology is evaluated via simulation using actual demand and yield data simulated from a distribution fit from historical data. Order release strategy and yield were found to be the dominant variables for complete and on-time orders without excess and shortages, and linear recursive control was found to be effective for tracking, monitoring and adjusting the release of parts into a single-piece flow job shop in an environment characterized by random and variable yield.

Corrective maintenance through dynamic work allocation and pre-emption: case study and application

This case study develops an innovative management and scheduling system for corrective maintenance of machines in a manufacturing facility. The study also involves a comparative evaluation of the proposed and the existing systems under a spectrum of operating conditions. A comprehensive simulation is used to evaluate system performances under a variety of settings which include reliability, service level, and cost consequences. The analysis is based on a full factorial experimental design. In summary, the developed self-regulating management system which involves dynamic work allocation and pre-emption is shown to yield higher machine availability and higher mechanic utilisation even with fewer mechanics. The study also finds that the new system is more streamlined, agile, and robust although it is subject to more-constrained machine reliability and mechanic service time environments. Further, a major reduction of current manpower can still achieve at least 95% machine availability, illustrating the cost effectiveness and efficacy of the developed system. This rule-based corrective maintenance system can be operated in uncertain environments on a real-time basis without additional reformatting costs and provides a competitive measure to deal with managerial issues such as low retention rate for skilled mechanics, highly uneven training levels and pay scales. The financial consequences and gains in strategic advantage with respect to the facilitys operational structure are promising after implementation. Moreover, the system developed in this case study represents a meaningful starting point for a more vigorous theoretical research on the bucket brigade system to different functions in industrial and operations management.

Increasing the effectiveness and cost‐efficiency of corrective maintenance using relay‐type assignment

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

Cost effective portable system for sign language gesture recognition

This paper presents a standalone system that converts static gestures into voice. It is also known as GesTALK. The primary input device is the self design and cost effective Data Glove. It operates in two basic modes. In first mode the system speaks a single alphabet for a static gestures made by the user, while in second mode the system speaks complete string by concatenating words. Various gestures of alphabets are made to spell out the words involved in string. This system has been shown to work for both American Sign Language (ASL) and Pakistan Sign Language (PSL) and other language models. Results show that the system recognizes 24 out of 26 letters; an overall accuracy of 90% is achieved.

Adaptive exponential smoothing versus conventional approaches for lumpy demand forecasting: case of production planning for a manufacturing line

Production planning in a lumpy demand environment can be tenuous, with potentially costly forecasting errors. This paper addresses the issue of selecting the smoothing factor used in lumpy demand forecasting models. We propose a simple adaptive smoothing approach to replace the conventional industrial practice of choosing a smoothing factor largely based on the analyst or engineers experience and subjective judgment. The Kalman filter approach developed in this study processes measurements to estimate the state of a linear system and utilises knowledge from states of measurements and system dynamics. Performances of an array of forecasting models that have been shown to work well in lumpy demand environments are compared with respect to the proposed adaptive smoothing factor and the conventional smoothing constant across a spectrum of lumpy demand scenarios. All models using the adaptive smoothing factor based on Kalman filter weighting function generate smaller errors than their conventional counterparts, especially under high lumpiness demand environments. Our proposed approach is particularly useful when production management is concerned about simplicity and transferability of knowledge due to constant personnel turnaround and low retention rate of expertise.

Fabrication and characterization of embedded horizontal micro‐channels using line‐scan stereolithography

Purpose – 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.Design/methodology/approach – Demonstration of the technique was performed using a 3D Systems Viper si2TM SL system and DSM Somos® WaterShedTM 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...

A case study of Bayesian belief networks in industrial work process design based on utility expectation and operational performance

Purpose - 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. Design/methodology/approach - 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. Findings - 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. Practical implications - 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 (

A paradigm for Group Technology cellular layout planning in JIT facility

). The study illustrates the use of an expert system and influence diagram to evaluate different alternatives for ergonomic work design in production process. Social implications - The results of this study can potentially improve health safety management and worker ergonomics. Originality/value - 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.