Research on packaging optimization in customized panel furniture enterprises

Various information systems have been implemented in most of the customized panel furniture companies in China, resulting in increased production difficulty and informational isolation. Enterprises need to adopt more systematic, scientific, and information-based methods to guide the production on the shop floor. Packaging optimization is important because it promotes sustainable development in furniture enterprise. Through the examination of the packaging process in customized panel furniture companies, this study investigated the bottleneck problems of the packaging process, which are predominantly focused on the calculation of the optimal packaging scheme and the upgrade of information systems. After exploring the theories and methods to solve the existing bottleneck problems, the heuristic algorithm was applied to obtain the optimal packaging schemes and complete the upgrade of packaging process information system. Based on the intelligent packaging software in company A, the Taguchi method was applied to find the best optimization parameters, which was proven effective in comparison with the original packaging solution. The number of packaging was decreased by 3.0%, and the amount of packaging corrugated paper decreased by 12.4. The packaging efficiency represented by the total packaging time showed a significant improvement despite the unit packaging time having increased by 2.0%.

Bottleneck Problems: An Information and Estimation-Theoretic View

Information bottleneck (IB) and privacy funnel (PF) are two closely related optimization problems which have found applications in machine learning, design of privacy algorithms, capacity problems (e.g., Mrs. Gerber’s Lemma), and strong data processing inequalities, among others. In this work, we first investigate the functional properties of IB and PF through a unified theoretical framework. We then connect them to three information-theoretic coding problems, namely hypothesis testing against independence, noisy source coding, and dependence dilution. Leveraging these connections, we prove a new cardinality bound on the auxiliary variable in IB, making its computation more tractable for discrete random variables. In the second part, we introduce a general family of optimization problems, termed “bottleneck problems”, by replacing mutual information in IB and PF with other notions of mutual information, namely f-information and Arimoto’s mutual information. We then argue that, unlike IB and PF, these problems lead to easily interpretable guarantees in a variety of inference tasks with statistical constraints on accuracy and privacy. While the underlying optimization problems are non-convex, we develop a technique to evaluate bottleneck problems in closed form by equivalently expressing them in terms of lower convex or upper concave envelope of certain functions. By applying this technique to a binary case, we derive closed form expressions for several bottleneck problems.

Research and Application of the Type about Rapid Prototyping Mold Bag Retaining Wall Applied to Filling Stope Drift Ends

Coal mining and filling connection is very fast in continuous mining and filling working face. How to build airtight walls at ends of filling stope drift efficiently is one of the bottleneck problems, which restricts production improving in continuous mining working face. This paper presented a design idea of the rapid prototyping mold bag wall, analyzed its structure, did much research and finally provided the design. Field application showed that it improved construction efficiency and reduced cost.