Lean production system design for fishing net manufacturing using lean principles and simulation optimization

Value stream mapping (VSM) is a useful tool for describing the manufacturing state, especially for distinguishing between those activities that add value and those that do not. It can help in eliminating non-value activities and reducing the work in process (WIP) and thereby increase the service level. This research follows the guidelines for designing future state VSM. These guidelines consist of five factors which can be changed simply, without any investment. These five factors are (1) production unit; (2) pacemaker process; (3) number of batches; (4) production sequence; and (5) supermarket size. The five factors are applied to a fishing net manufacturing system. Using experimental design and a simulation optimizing tool, the five factors are optimized. The results show that the future state maps can increase service level and reduce WIP by at least 29.41% and 33.92% respectively. For the present study, the lean principles are innovatively adopted in solving a fishing net manufacturing system which is not a well-addressed problem in literature. In light of the promising empirical results, the proposed methodologies are also readily applicable to similar industries.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

Biodegradability Study of the Biosurfactant Contained in a Crude Extract from Corn Steep Water

Over the last few years, the global biosurfactant market has raised due to the increasing awareness among consumers, for the use of biological or bio-based products. Because of their composition, it can be speculated that these are more biocompatible and more biodegradable than their chemical homologous. However, at the moment, no studies exist in the literature about the biodegradability of biosurfactants. In this work, a biosurfactant contained in a crude extract, obtained from a corn wet-milling industry stream that ferments spontaneously in the presence of lactic acid bacteria, was subjected to a biodegradation study, without addition of external microbial biomass, under different conditions of temperature (5–45 °C), biodegradation time (15–55 days), and pH (5–7). For that, a Box–Behnken factorial design was applied, which allowed to predict the percentage of biodegradation for the biosurfactant contained in the crude extract, between the range of the independent variables selected in the study, obtaining biodegradation values between 3 and 80%. The percentage of biodegradation for the biosurfactant was calculated based on the increase in the surface tension of samples of the crude extract. Furthermore, it was also possible to predict the variation in t_1/2 for the biosurfactant (time to achieve the 50% of biodegradation) under different conditions.     

Malic acid production from renewables: a review

Malic acid derived from fossil resources is currently applied in the food and beverage industries with a medium global production capacity. However, in the transition from a fossil-based to a bio-based economy, biotechnologically produced l -malic acid may become an important platform chemical with many new applications, especially in the field of biopolymers. In this review, currently used petrochemical production routes to dl -malic acid are outlined and insights into possible bio-based alternatives for microbial l -malic acid production are provided. Besides ecological reasons, the possibility to produce enantiopure l -malic acid by microbial fermentation is the biggest advantage over chemical synthesis. State-of-the-art and open challenges concerning production host engineering, substrate choice and downstream processing are addressed. With regard to production hosts, a literature overview is given covering the leading natural production strains of Aspergillus, Ustilago and Aureobasidium, as well as Escherichia coli as the most important engineered recombinant host. The utilization of renewable substrates as an alternative to glucose is emphasized in particular as a key aspect for a competitive bio-based production. Out of the alternative substrates discussed in this review, the industrial side-streams crude glycerol and molasses seem to be most promising for large-scale l -malic acid production. © 2019 The Authors. Journal of Chemical Technology & Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

高效AVS音频上下文位平面编码器设计

研究了AVS音频编码标准中上下文位平面编码算法,分析了编码算法的特点。通过对上下文平面编码算法的优化,提出了一种适合ASIC实现的硬件结构,通过合理设计二级流水线,能近似达到每时钟1比特矢量的编码速率,在保证编码速度前提下大幅降低了硬件资源。     

密码理论算法综述

概要介绍了密码理论算法的发展现状，重点讨论了密码算法中的布尔函数，最后总结了各种密码体制的应用。     

最新的ITU-T嵌入式变速率语音编码关键技术

介绍了ITU-T的新一代语音编码标准G.729.1的编码器、译码器原理,讨论了此标准实现码流嵌入式所采用的关键技术:嵌入式的码激励线性预测编码技术、时域频带扩展技术以及时域混叠抵消的预测变换编码技术,并通过客观评测验证了G.729.1语音编码标准的高性能。     

钻井井喷失控井喷流出口速度预测方法研究

失控井喷流出口速度、喷口内压力、喷层产量都是井喷失控处理方案设计、作业施工中重要的基础数据。由于井喷失控井井口环境条件复杂，井喷失控后无法在井口安装测量仪表及在高速喷流中放入参照物，不能直接获取以上数据。文章利用地质、钻井过程获得的地层物性参数和气体动力学方程，探讨井喷失控井天然气喷流在不同井筒流动尺寸及组合的喷流速度预测模型，可应用薄剪切模型或RNG修正的k-ε模型定量描述速度场、温度场、浓度场颁。为井喷失控井处理方案设计、施工作业提供基础数据。     

浅述设备对PCB微孔电镀镀液更新之影响

分析了设备对PCB电镀过程中孔中镀液更新之影响,为有效地利用设备条件改善孔中镀液的更新提供了一些方法及理论数据。