Disciplined autonomy: How business analytics complements customer involvement for digital innovation

The rise of big data and the fluid boundaries of digital products are driving companies to use business analytics (BA) to power their customer involvement. The complementarity view offers unique competence to generate value from BA because capability complementarity is less likely to be replicated or imitated. Unlike prior studies on BA-enabled value realization, our research investigates the interactions of BA and customer involvement capabilities using the complementarity view. We tested our model using data collected from 317 IT companies in China. Our results suggest that BA value realization requires both a top-down mechanism in which BA skills provide global guidance for alignment with a company’s goals and a bottom-up mechanism in which BA culture empowers local autonomy for adaptation to ever-changing needs. Our BA-complemented mechanisms provide research and practice with a way to concurrently use BA and customer involvement capabilities to address the duality of digital innovation. We further suggest that BA skills are necessary but insufficient for digital innovation because BA culture demonstrates a stronger effect in complementing organizations’ existing capabilities than BA skills do.     

Neural network classifier and multiple hypothesis image segmentation for dietary assessment using calorie calculator

Nowadays, dietary assessment becomes the emerging system for evaluating the person’s food intake. In this paper, the multiple hypothesis image segmentation and feed-forward neural network classifier are proposed for dietary assessment to enhance the performance. Initially, the segmentation is applied to input image which is used to determine the regions where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the significant feature of food items is extracted by the global feature and local feature extraction method. After the features are obtained, the classification is performed for each segmented region using feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food area volume and (ii) calorie and nutrition measure based on mass value. The outcome of the proposed method attains 96% of accuracy value which provides the better classification performance.     

Displacement field denoising for high-temperature digital image correlation using principal component analysis

Principal component analysis (PCA) was extended to minimize the noise effect in digital image correlation (DIC) measurement under a high-temperature atmosphere environment. First, the principle of PCA was introduced, and the singular vectors and singular values for each component of the displacement fields from DIC were obtained. Then, the simulated high-temperature speckle images were developed to investigate the influences of noise on the DIC method under a high-temperature environment. Finally, the displacement fields of several special conditions were extracted from the simulated speckle images and experimental images; the effects of noise on the PCA were also analyzed.     

Managing supply systems with partial information on shipment locations

This paper studies a supply system for a retailer who orders a single product from one manufacturer. Orders filled by the manufacturer pass through multiple transportation stages before reaching the retailer. Each stage represents either a physical location or a step in the delivery process. The lead time for a new order depends on the location of shipments against prior orders in transit. Shipments are not allowed to cross over in time. Thus, the movement of each shipment depends on the movements of shipments ahead of it and the resulting congestion. The retailer is able to track shipments as they move through the transportation channel. The retailer adopts an ordering policy that minimises the sum of his one-period holding and shortage costs, using available status information of shipments already in transit. The case where practical constraints prevent the retailer from obtaining a complete status of shipments at all stages in the transportation channel is considered. The methodology developed evaluates the value of partial shipment tracking information, and uses it to determine the optimal placement of a limited number of tracking devices. The methodology can also be used to evaluate the cost–benefit of placing additional tracking devices in the supply system.     

Decentralised decision-making with information sharing vs. centralised decision-making in supply chains

In recent years, implementing coordination mechanisms in decentralised supply chains to reduce the well-known negative effects of decentralisation, such as the ‘bullwhip effect’, has become a considerable challenge. Furthermore, with the dramatic developments in information and communication technologies, real-time information sharing has become increasingly easier to implement. In this work, we study a mono-product divergent supply chain composed of a supplier, a warehouse, retailers and customers in the context of decentralised and centralised decisions. The main objective of this study is to compare a decentralised supply chain combined with different scenarios of simultaneous upstream and downstream information sharing vs. a centralised supply chain. A mathematical model is developed to compare the logistics costs in the two decision contexts. The experimental results clearly show that the simultaneous sharing of customer demand and supplier-warehouse lead time information in a decentralised supply chain yields nearly equivalent logistics costs as the centralised supply chain context. However, the main beneficiary of the sharing is the warehouse, which receives approximately two-thirds of the benefit. Thus, incentives and revenue sharing contracts should be implemented to motivate and balance the benefits between supply chain partners.     

Research on lease and sale of electric vehicles based on value engineering

Electric vehicles (EVs) acknowledged as potential means of transportation tools in the near future are widely accepted as the development trend of automobile industry due to its environment protection and fuel energy saving properties. As a product containing new technologies and concepts with little market experience and consumer identification, studying its life cycle operation modes will help to figure out an optimal approach to conduct EVs manufacturing and service. The two common operation modes, lease and sale of EVs, have their own advantages and weaknesses under different scenarios and consumer psychological status. Research and comparisons on the function, cost and value of two operation modes in full life cycle will simulate the rapid development of EVs forming a mature and dynamic operation mechanism. This paper utilised approaches in value engineering, putting forward customer requirements and technical elements of EV lease and sale based on quality assessment and customer-perceived value, proposing the metric method of function and cost coefficient by mathematical modelling, and conducting value coefficient analysis and comparison based on customer’s risk aversion psychology. An illustrative example raised for studying operation mode of three different kinds of EVs based on the analysis of value coefficient, providing guideline for manufacturer and servicers of EVs.     

低逾渗MWCNTs-CB/UHMWPE导电复合材料的制备及性能

采用溶液法及机械共混法分别制备了均匀结构的炭黑(CB)/超高分子量聚乙烯(UHMWPE)及隔离结构的多壁碳纳米管(MWCNTs)-CB/UHMWPE复合薄膜。扫描电镜分析显示,虽然大部分CB均匀分散于UHMWPE基体中,但依然存在明显的局部团聚,而隔离结构中的MWCNTs-CB分布于UHMWPE界面间,更易形成导电通道。导电测试结果表明,复合材料的导电逾渗值由均匀分布的4.91%(体积分数)下降到隔离结构的0.42%。MWCNTs的加入完善了CB间的导电网络,使复合材料的逾渗值进一步下降,当CB∶MWCNTs=15∶1时,复合薄膜的逾渗值由0.42%(体积分数)下降到0.24%,然而混合填料中MWCNTs含量的进一步增加几乎对逾渗值没有影响。力学性能研究表明,隔离型复合材料的拉伸强度和断裂伸长率随填充剂含量的增加呈现出先上升后下降的趋势。     

AZ31镁合金室温拉伸微观变形机制EBSD原位跟踪研究

利用电子背散射衍射(EBSD)技术,原位跟踪AZ31镁合金轧制板材室温下沿轧向拉伸时的晶粒取向变化。对变形过程的滑移系和孪晶启动机进行分析。结果表明:变形过程主要由〈a〉基面和柱面滑移系开动而实现,晶粒取向无明显变化,大量〈a〉位错滑移的产生,使得变形后小角度晶界增加明显。晶粒中拉伸孪晶是试样在拉伸变形过程中产生的,而非在试样拉伸后的卸载过程中产生。     

旋转状态下微波叶尖间隙传感器校准影响因素分析

主要针对应用于发动机叶尖间隙测量的微波叶尖间隙传感器的校准需求,对测量原理、传感器的校准原理等进行了详细阐述,并分析了转速和回缩值等对校准结果的影响。为微波叶尖间隙传感器的进一步优化设计及应用提供了数据依据。     

基于ANSYS强度仿真与动力学测试的包装结构优化设计

目的 在保障机械结构强度的前提下,对消费量大的某泵用木包装结构进行优化设计,对机械强度进行CAE有限元仿真,并进行振动跌落冲击测试,以降低成本提高产品价值。方法 首先分析产品的使用功能,设计新型包装方案,将原有铁底板支撑结构优化改为用材更少的V型木质支撑结构,建立力学模型,进行底强度分析以及稳定性计算;然后运用SolidWorks建立3D模型,运用ANSYS Workbench进行仿真评估;最后生产出新型包装,并根据包装测试标准进行了测试。结果 新的包装结构用V型木质取代了铁底板支撑,节约了100%的铁质包装材料,并通过了冲击振动跌落测试。优化设计的新包装型式能满足运输过程中的冲击振动跌落等产品保护要求,满足运输稳定性的功能要求。结论 本文以价值工程理念为指导,优化设计的新包装结构,在满足产品功能的同时节约了成本,是价值工程在包装优化领域极好的运用,为机械工程领域包装工程师提供了设计参考和解决方案。