Development of a Rapid Prototyping System using Response Surface Methodology

This case study presents an investigation of the relationships between eight process operating variables (factors) and five part performance measures (responses) in a rapid prototyping system. The use of fractional factorial, single‐factor foldover, and central composite designs is demonstrated. Polynomial regression models are constructed for each response, followed by a desirability function model. Canonical and ridge analyses are used to identify a group of factor settings that simultaneously produce improved performance for all responses. Copyright © 2006 John Wiley & Sons, Ltd.     

Investigation on the determination of flow direction using two parallel cylindrical hot film sensors

Measurement of instantaneous air flow velocity with high frequency can be carried out by using a hot wire anemometer (HWA). HWA works on the basis of heat transfer rate from hot wire to the fluid flow, therefore directional identification of the air flow using hot wire anemometer is a difficult task. By using two parallel cylindrical hot film sensors a probe was built. By considering the wake and heat effect of the upstream sensor on the downstream sensor, direction of the air flow can be identified. In this work, the wake and heat effect resulting from the upstream sensor to the velocity measurement, by the downstream sensor was studied. This measured velocity is dependent of the following factors namely; air velocity, upstream sensor overheat ratio, distance between the two sensors and turbulence intensity of the flow. As a result it was found that the manufactured probe with sensor distance of 1 mm apart is capable of measuring reverse flow measurements of up to 20 m/s for a moderate turbulent flow.     

The influence of build strategies in selective inhibition sintering (SIS)

Selective Inhibition Sintering of metal alloys (SIS-metal) has been proven effective in the additive manufacture (AM) of low resolution bronze parts. Recent advancements in the use of a high-precision inkjet print head represented an order of magnitude improvement in SIS-metal resolution. However, the fabrication of complex three-dimensional metallic parts required new SIS-metal compatible, cross-sectional image generation based on the part boundary profile. In the proposed study, five candidate layer-processing approaches were identified and validated for basic geometries. These approaches were chosen from previous research as well as preliminary investigations and were applied to a modified SIS-metal process for validation. The validation criteria were based upon the amount of powder waste produced, the ability to handle complex geometries, printing speed, extraction (post-processing) speed, and part integrity. Results are discussed for implementation of the five candidate layer processing approaches in the fabrication of basic shapes. A preliminary evaluation is presented for their use on more complex geometries. Two approaches were then chosen for the construction of more complex geometries, the results of which are presented.     

Aggregate planning models incorporating productivity—an overview

Most aggregate planning models utilize a constant productivity factor throughout the planning horizon. Recently new work has been done to incorporate changing productivity factors into aggregate planning models; however, some of these models have certain limitations and unrealistic assumptions. The objective of this paper is to present an overview of the state of the art in combining aggregate planning models with learning curve productivity considerations.     

Generation of alternative process plans in integrated manufacturing systems

The availability of alternative process plans is a key factor for integration of design, process planning, and scheduling functions. The availability of alternative process plans can speed up the process of incremental process plan generation which can help in providing real time cost feed back to the designer after each design modification. Also alternative process plans relax the constraints in the optimization of production schedules, which in turn results in more efficient use of production resources and better delivery schedules. This paper describes a methodology for generation of alternative process plans in the integrated manufacturing environment. The procedure consists of: selection of alternative machining processes, clustering and sequencing of machining processes, and generation of a process plan network. Each of these steps is explained in detail. The result of the procedure is the process plan network that provides all alternative process plans for the given part. Methods for the selection of an optimal process plan are also described. Computational complexity of the procedure is discussed and experimental results on several realistic examples are shown.     

Analysis of a deterministic power level selection algorithm with small and large power steps for Aloha networks under saturation

Standard power control techniques are not deployable in Aloha networks due to lack of central controlling entity and/or inefficiency of such algorithms in large networks with bursty traffic. To handle this problem in practice, simple transmission power selection algorithms are used for ranging and/or combating harsh channel conditions. In such algorithms, the transmission power is steadily increased by an amount called power step, until the packet is successfully transmitted. Noting that ranging is the major concern of this approach, small power steps are ideal for its operation. However, as we will show in this paper, using small power steps with this algorithm causes a throughput collapse in large networks, when capture effect is considered in the analysis. In the asymptotic case, the throughput of this algorithm will be less than the throughput of the Binary Exponential Backoff (BEB) scheme which only uses a single power level. To show these results, we will present an asymptotic analysis of this algorithm with small power steps in an ideal communication channel where BEB is used as the retransmission scheme. In order to strengthen the results, we will prove the existence of better choices for power steps by extending the analysis for large power steps and we will show that properly chosen large power steps guarantee higher throughputs and require approximately the same average powers as small power steps. Our analysis and simulation results show that small power steps should be avoided with the mentioned power selection algorithm except probably for ranging and once the ranging process is complete, larger power steps should be used to exploit the capture effect.

The dynamic impact of renewable energy consumption and financial development on CO2 emissions: For selected African countries

This empirical study examines the impact of economic growth, renewable energy, energy consumption, financial developments, trade openness, and urbanization growth on CO₂ emissions using the Pooled Mean Group (PMG) approach and Granger Causality in the EKC model a data set of 25 African countries over the period 1985–2015. The results showed that increases in renewable energy consumption and trade openness decrease CO₂ emissions, and the EKC hypothesis is supported for the African countries. Granger’s causality results indicated the presence of bidirectional causality between economic growth and financial development and CO₂ emissions. These results could support policymakers manage financial development and consider clean investments and other ecological aspects for sustainable urban development. The causality tests showed a unidirectional causality running from renewable energy consumption to CO₂ emissions in African countries.     

Process sequencing and process clustering in process planning using state space search

Process sequencing, as a very important part of process planning, has been the subject of many research reports in the area of process planning, but is usually treated as a feature-sequencing problem. This paper presents a novel algorithm for process sequencing, which considers the feature precedence network, different process candidates, and machine and tool constraints. The algorithm consists of two parts: process clustering and process sequencing. For clustering we used a notion of the same resource usage for different features, while for sequencing we applied the best-first search method algorithm to generate an optimal process sequence. The algorithm has been applied on several examples with realistic complexities, and it showed satisfactory results.     

Integration of process planning and scheduling— a review

In recent years, a few researchers have addressed the need for the integration of process planning and scheduling functions in order to achieve superior overall system performance. Many of these researchers have discovered that the potential savings are substantial when process planning and scheduling are integrated. It has been reported that typical scheduling objectives, such as minimizing makespan, maximizing equipment utilization, etc, can be significantly improved as the result of integration of these two important manufacturing system functions. In this paper, we present a review of the reported research in this area, discuss the extent of applicability of various approaches, and suggest directions for future research.