Sherri L. Messimer

A weighted variance capability index for general non‐normal processes

Process capability indices are considered to be one of the important quality measurement tools for the continuous improvement of quality and productivity. The most commonly used indices assume that process data are normally distributed. However, many studies have pointed out that the normally-based indices are very sensitive to non-normal processes. Therefore we propose a new process capability index applying the weighted variance control charting method for non-normal processes to improve the measurement of process performance when the process data are non-normally distributed. The main idea of the weighted variance method is to divide a skewed or asymmetric distribution into two normal distributions from its mean to create two new distributions which have the same mean but different standard deviations. In this paper we provide an example, a distribution generated from the Johnson family of distributions, to demonstrate how the weighted variance-based process capability indices perform in comparison with another two non-normal methods, namely the Clements and Johnson–Kotz–Pearn methods. This example shows that the weighted variance-based indices are more consistent than the other two methods in estimating process fallout for non-normal processes. Copyright

Overhanging Features and the SLM/DMLS Residual Stresses Problem: Review and Future Research Need

A useful and increasingly common additive manufacturing (AM) process is the selective laser melting (SLM) or direct metal laser sintering (DMLS) process. SLM/DMLS can produce full-density metal parts from difficult materials, but it tends to suffer from severe residual stresses introduced during processing. This limits the usefulness and applicability of the process, particularly in the fabrication of parts with delicate overhanging and protruding features. The purpose of this study was to examine the current insight and progress made toward understanding and eliminating the problem in overhanging and protruding structures. To accomplish this, a survey of the literature was undertaken, focusing on process modeling (general, heat transfer, stress and distortion and material models), direct process control (input and environmental control, hardware-in-the-loop monitoring, parameter optimization and post-processing), experiment development (methods for evaluation, optical and mechanical process monitoring, imaging and design-of-experiments), support structure optimization and overhang feature design; approximately 143 published works were examined. The major findings of this study were that a small minority of the literature on SLM/DMLS deals explicitly with the overhanging stress problem, but some fundamental work has been done on the problem. Implications, needs and potential future research directions are discussed in-depth in light of the present review.

Simulation and undergraduate engineering education: the technology reinvestment project(TRP)

This paper discusses an undergraduate engineering education program recently funded by the advanced research projects office (ARPA) technology reinvestment project (TRP) to add more hands-on experience for undergraduate engineering students.

An Empirical Study of the Relationship of Stability Metrics and the QMOOD Quality Models Over Software Developed Using Highly Iterative or Agile Software Processes

The purpose of our study is to analyze whether the Bansiya and Davis quality models also reflect the ongoing stability of a software design in software developed using a highly iterative or agile process. We performed an empirical study over multiple iterations of various software packages developed using highly iterative or agile methods. We examined several Bansiya and Davis quality factor models (reusability, flexibility, understandability, functionality, extendibility, and effectiveness) over this data set and we compared them to stability metrics. We conclude that the Bansiya and Davis total quality index does indeed reflect stability over the data sets examined.

Measuring technology transfer performance: A case study

The debate continues on how to measure results of technology transfer. New and revised models are being conceived and tested in various economic settings. This paper addresses the performance measures that are being derived from the Huntsville/Madison County Chamber of Commerce technology transfer program.

Evaluation of Ozone Pretreatment on Flux Parameters of Reverse Osmosis for Surface Water Treatment

This research details the effects of ozone pretreatment on flux of a reverse osmosis membrane. Initial tests were conducted to determine the effects of ozonation on solids removal, turbidity, and chemical oxygen demand concentrations using various doses on a simulated surface water. These initial tests showed that the best reduction of solids in the 2–5 microns range was at 0.30 mg/L of ozone. Next, a series of bench scale tests was run for 62.5 hours using a standard reverse osmosis system under constant pressure with three pre-ozonation doses and a no ozone baseline dose. Temporal models were developed using the flux data from these tests to determine the effects of operating hours and ozone dosage on flux. It was found that the laboratory data were not linear and followed power law models. Statistical analysis was used to determine the significance of each ozone dose on the four developed models. The change in flux over the 62.5 operating hours with an ozone dosage of 0.30 mg/L showed the lowest flux change. Last, the models were tested using Hermias filtration models and resistance versus time data to determine the type of membrane fouling that existed. It was concluded that the major fouling was pore blockage. This work demonstrated that ozone pretreatment is effective prior to use with reverse osmosis since it shows a better solid and organic removal rate as well as decreased flux and resistance changes over time.

Anti-fragmentation in aversion dynamics scheduling

Aversion dynamics (AD) scheduling is a general approach used to create special job sequences that reduce (mitigate) the potential negative impacts associated with events such as machine upgrades or repairs. Upgrades and repairs may go as planned, but they can also be unstable processes that require one or more shifts until performance re-stabilizes to a steady-state level. To consider these phenomena, special AD sequences are constructed using hybrid scheduling heuristics that combine an underlying heuristic for robust performance throughout the scheduling horizon and a specialized modifying heuristic for time periods around the anticipated event. Previous research into the behaviour of the AD heuristics examined the deterministic and stochastic characteristics of the problem and investigated the benefits associated with special job sequencing around known and anticipated events. This research explores the concept of protecting priority jobs around the anticipated event to ensure that the high-valued or important jobs do not become fragmented by the interruption. A fragmented job may require additional set-ups and the integrity of the entire job may be questionable if the process is stopped and then restarted after a repair or upgrade. This paper proposes a strategy that incorporates information regarding how far into the impact zone a job will run to determine if the job should be delayed until the risk has decreased. Sensitivity experiments will be reported to provide insight into the tradeoffs that occur in the immediate time horizon—just before and after an event takes place. Experimental results indicate that fragmentation can be significantly reduced in many cases with only a small impact on the weighted tardiness objective function.

Object pose determination from range data

Abstract This paper is concerned with determining the position and orientation of a three-dimensional object from range data. An algorithm is presented which uses an enclosing object and the central moments for an initial estimate of pose. A refined estimation is obtained by a nonlinear least squares technique. The use of an enclosing object reduces the number of parameters which must be solved for by the nonlinear least squaes estimation. An object representation based on a relational graph of superquadric primitives is used for description so that the method is applicable for 3-D objects of general shapes.

Genetic Algorithm Optimization of a Filament Winding Process Modeled in WITNESS

Abstract With the advent of smaller, less expensive, and generally more effective computers, simulation models have become increasingly popular tools for solving engineering problems. More and more, engineers are turning to simulation environments to achieve increased system performance at a reduced cost. One such environment found to be very effective is WITNESS, a modeling program developed by AT&T and Istel. This article describes an effort to link a genetic algorithm with WITNESS to optimize a model of a manufacturing process called filament winding. Results show the genetic algorithm to be an effective, optimization tool for use with WITNESS models.

Incorporating environmental issues in a filament winding composite manufacturing system simulation

This paper presents SimBuilder, a simulation system incorporating environmental and quality concerns into a traditional manufacturing simulation environment. These simulations can be used to generate a complete material balance around a particular manufacturing process and can be made available to design engineers to aid in life cycle design assessments. An example developed for the filament-winding composite manufacturing industry is presented.