Optimization Of Process Efficiency Research Articles

Analysis of process efficiency in laser fusion cutting and some single- and multi-objective optimization aspects

For an efficient use of laser cutting technology, it is of great importance to analyze the impact of process parameters on different performance indicators, such as cut quality criteria, productivity criteria, costs as well as environmental performance criteria (energy and resource efficiency). Having this in mind, this study presents the experimental results of CO2 laser fusion cutting of AISI 304 stainless steel using nitrogen, with the aim of developing a semi-empirical mathematical model for the estimation of process efficiency as an important indicator of the achievable energy transfer efficiency in the cutting process. The model was developed by relating the theoretical power needed to melt the volume per unit time and used laser power, where the change of kerf width was modeled using an empirical power model in terms of laser cutting parameters such as laser power, cutting speed, and focus position. The obtained results indicated the dominant effect of the focus position on the change in process efficiency, followed by the cutting speed and laser power. In addition, in order to maximize process efficiency and simultaneously ensure high cut quality without dross formation, a laser cutting optimization problem with constraints was formulated and solved. Also, a multi-objective optimization problem aimed at simultaneous optimization of process efficiency and material removal rate was formulated and solved, where the determined set of Pareto non-dominated solutions was analyzed by using the entropy method and multi-criteria decision analysis method, that is, the Technique for Order of Preference by Similarity to Ideal Solution. The optimization results revealed that in order to enhance process efficiency and material removal rate, while ensuring high cut quality without dross formation, focusing the laser beam deep into the bulk of material is needed with particular trade-offs between laser power and cutting speed levels at high pressure levels of nitrogen.

Integrated energy analysis of cutting process and spindle subsystem in a turning machine

This paper presents a novel approach for systematic energy efficiency evaluation and optimization in turning operations, combining spindle, chiller and material removal models. Framing a joint machine-process design approach, the proposed study aims at selecting optimal combinations of cutting parameters (feed rate, depth of cut and spindle speed) for a given spindle-chiller assembly, able to minimize the energy consumption. Contrary to most of the literature, where the efficiency analysis is fully empirical, relying on extended cutting test campaigns, here a model-based approach is adopted. The goal is to characterize a key subsystem of modern machine tools, often used in both turning and milling machines, composed by a permanent magnet brushless direct-drive spindle with a dedicated chiller unit. Analytical relationships are identified, producing efficiency maps as a function of various process parameters. Physic-based models are exploited, reproducing electrical and mechanical energy dissipation occurring in the spindle and chiller units and in the material removal process. The models parameters are identified by a reduced set of spindle ramp-up and cutting tests, executed in an industrial context. Then, an overall process efficiency optimization is performed and discussed.

A Two‐Stage Service Replica Strategy for Business Process Efficiency Optimization in Community Cloud

Business process that facilitates the organization cooperation and resource sharing plays an important role in Community cloud (Comc). The nature of applications and decentralized infrastructure in Comc make it a big challenge in ensuring the execution efficiency of business process, especially when the business requests are in high concurrency. We present a two-stage service replica strategy to improve the execution efficiency of business process by shortening the response time of request to single service and reducing interaction time among distributed services. We initially utilize the social network property of services to pre-allocate the replicas of key services. After that, queueing model is adopted to determine the required additional replicas according to the quantity and frequency of user requests, then schedule service replicas and requests dynamically. Experiments demonstrate the effectiveness of the proposed strategy.

Approaches to Product Development and Innovation

In this column Cauvain describes the drivers behind and processes involved in product development and innovation in the baking industry. There are many drivers behind innovation and the development of new products, including quality optimization, reduction of product variability, optimization of process efficiency, and reduction of manufacturing costs. In some cases, we are forced to innovate because of external pressures on raw material availability and pricing; new government regulations; or changes in consumer demands. The processes associated with innovation are more singular—at least to the extent that they comprise having an idea, trying out different ideas, and moving progressively upward in scale. Ultimately the human factor in new product development remains a critical factor. This is especially true for innovation, which often requires thought processes that involve “breaking the rules” or “thinking outside the box.” The process of innovation requires the assembly of a wide range of knowledge to...

Optimization of a Closed Die Forging Process to Manufacture a Gear Wheel by the Use of a Response Surface Model

Heavy-duty components used in the automotive industry, in wind turbines and in many other industrial applications are often produced using hot forging processes. Nowadays the design of hot forging processes aims for the optimization of process efficiency on the one hand and final mechanical product properties on the other hand. Excellent mechanical properties needed for hot-forged components e.g. high load capacity and high fatigue resistance depend on a fine homogeneous microstructure distribution across the final product’s cross-section. Efficiency in hot forging can be optimized by increasing the temperature during processing, which allows for lower forging loads and lower die stresses, thus improving die life in terms of mechanical fatigue. To guarantee for a fine homogenous microstructure across the cross section of the forged good, dynamic recrystallization (DRX) has to be initiated during deformation and Grain Growth (GG) has to be avoided during dwell times and cooling. Due to the high computational costs of finite element simulations an optimization aiming for lowest possible forging loads and finest possible grain sizes is very time-consuming. In this paper a Response Surface Model (RSM) of the forging process is introduced, which allows for much faster evaluation of the outcome of forging simulations, albeit by interpolation of simulation results, and thus allows for optimization. The information required to create the RSM is obtained by Design Of Experiments (DOE) techniques using an FE-model of the forging process which was calibrated earlier. The process variables considered include the initial temperature of the billet and the die kinematics. Subsequently, an optimization algorithm is combined with the RSM to find the design variables giving minimum possible loads during deformation and finest possible grain sizes in the forged product. The RSMs results are validated by the use of the existing FE-model.

Autothermal and allothermal pyrolysis in a continuous fixed bed reactor

Pyrolysis plays a major role in the optimization of process efficiency and gas quality in two-stage gasifiers. We developed an original reactor at pilot scale to investigate continuous fixed bed pyrolysis, in either allothermal or autothermal operating mode using air injection. Instrumentation and analysis enabled thermal profiles to be established inside the bed along with fine measurement of yields, char composition, permanent gases, and compounds at the outlet of the pyrolysis reactor. Under oxidative conditions, fixed-bed pyrolysis led to smoldering and the stabilization of an ignition front between 10 and 20cm below the bed surface. With oxidative pyrolysis, yields of organic condensates were lower than with allothermal pyrolysis, whereas the production of pyrolysis water and permanent gases increased considerably. The main conclusion is that during autothermal pyrolysis in fixed-bed conditions, the presence of oxygen promotes oxidation of volatile matter and cracking reactions, thereby increasing the production of pyrolysis water and permanent gases. We observed a significant increase in yields of CO2 and CO, while the yield of char remained comparable to that in allothermal experiments.

Ex situ bioprocess monitoring techniques

Rapid development of biotechnology resulted in increasing need for bioprocess monitoring and control. Efficient process control allows optimization of process efficiency and productivity, reduction of costs and pollution, and quality control. In situ sensors for real-time bioprocess monitoring have been recently reviewed. In this paper the use of ex situ techniques for real time (or quasi real time) monitoring methods is reviewed. These include mass spectrometry, gas chromatography, methods based on semiconductor gas sensors and electronic noses for the analysis of dissolved gas and bioreactor head-space, and on-line liquid chromatography and capillary electrophoresis, spectroscopy and biosensors for monitoring of the bulk process media. Flow techniques allow for the analysis to be carried out ex situ, out of the reactor reintroducing various detection methods that are impossible to implement in an in situ set-up. Because of their versatility flow analysis techniques (continuous and segmented flow analysis, flow injection analysis, sequential injection analysis and bead injection analysis) are broadly used for sample handling and analysis of the bulk media, and their applications in bioprocess monitoring are discussed.