The line-cell (or line-seru) conversion is an innovation of assembly systems that has received less attention. Its essence is dismantling an assembly conveyor line and adopting a mini-assembly unit, called seru (or cell). In this paper, we discuss how to do such line-cell conversions, especially focusing on assembly cell formation (ACF) and assembly cell loading (ACL). We perform 64 arrays of full factorial experiment analysis that incorporate three factors: work stations, product types, and product lot sizes. We construct a two-objective line-cell conversion model that minimises the total throughput time (TTPT) and the total labour hours (TLH). Three non-dominated solutions obtained from the two-objective model are used to evaluate the performance of the line-cell conversion. By investigating the experimental results of the ACF and the ACL, we summarise several managerial insights that could be used to help successful line-cell conversions.

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As a new paradigm of information technology, the Internet of Things (IoT) is attracting increasing attention from various industrial fields. It is foreseeable that the applications of IoT will be prevalent in the public transportation system and bring changes to the system in the near future. In this paper, we analyze the impact of IoT environment on the public transportation system, propose a new framework of the intelligent public transportation system based on IoT, and present the deployment of the elements, the communication network, and the three-tier architecture of the system in detail. We also present the information flow, technical scheme, optimization model, and algorithm of the main modules of dynamic optimization of the system. The innovative points of this paper lie in: (1) a new framework for public transport system based on IoT, which integrates the scheduling problems of subway, bus, and shared taxi, is proposed for better-coordinated transfer solutions; (2) transport flow prediction methods based on periodic patterns mining is proposed for road flow analysis and passenger flow analysis, and; (3) mathematical model and DSS-based evolutionary computation algorithm are proposed for solving the dynamic bus scheduling and controlling problems. The proposed intelligent transport system based on IoT can assist the decision makers to increase the utilization rate of the transport resources, improve the efficiency of scheduling, and reduce passengers' traveling time.INDEX TERMS Public transportation system, dynamic scheduling, traffic flow, the Internet of Things.

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