The manufacturing industry faces the challenge of small and diversified customer orders. To meet this challenge, strong internal production capabilities are required. A lean manufacturing process that uses fewer resources and offers greater process improvement will help SMEs to continue to contribute to the global economy. Though SMEs provide most employment opportunities, previous studies have focused on large companies in auto-manufacturing-related industries. With the commitment and support of the management, and the application of a value stream map (VSM) and related improvement tools, we produced a practical process improvement model for a lean manufacturing system in an SME. With the commitment and support of the management and the joint efforts of the project improvement staff, the 10 improvement projects over a six-month period all achieved their goals: reduction in lead time from 26 days to 19.5 days, improvement of welding per people per hour (PPH) efficiency by 28.3%, improvement of packaging PPH efficiency by 64.1%, improvement of working in process (WIP) efficiency at the production site by 83.84%, and improvement of raw material storage by 83.84%. The efficiency of the raw material warehouse inventory was improved by 58.63%, and the efficiency of the shipment completion rate was improved by 14.5%.

When threatened with catastrophic political or economic fluctuations, a firm might be forced to consider relocating their supply chain to reduce the risk. Such a relocation necessitates a series of changes, so making the right decision is crucial for sustainable development of the company. In the past, various models have been developed to help managers to select the optimal location. However, most of these considered the factors independently but in the real world, these factors have a mutually influential relationship. This study purposes a hybrid multiple criteria decision making (MCDM) model to provide decision makers with a comprehensive framework to evaluate the best strategies to solve relocation problems, which also considers the interdependency between criteria. The model incorporates the DANP (Decision Making Trial and Evaluation Laboratory-based Analytic Network Process) model (subjective weight) and entropy method (objective weight) to determine the weights of the criteria. Then, the modified VIKOR (VIšekriterijumsko Kompromisno Rangiranje) method is applied to select the optimal alternative for relocation. The usefulness of the model is demonstrated by taking an electronics manufacturing company with a global supply chain as an example. The results indicate that the proposed hybrid model can assist companies in choosing the best locations for their supply chains for sustained development.

The Internet of Things (IoT) has become critical to the implementation of Industry 4.0. The successful operation of smart manufacturing depends on the ability to connect everything together. In this research, we applied the TOC (Theory of Constraints) to develop a wireless Wi-Fi intelligent programmable IoT controller that can be connected to and easily control PLCs. By applying the TOC-focused thinking steps to break through their original limitations, the development process guides the user to use the powerful and simple flow language process control syntax to efficiently connect to PLCs and realize the full range of IoT applications. Finally, this research uses oil–water mixer equipment as the target of continuous improvement and verification. The verification results meet the requirements of the default function. The IoT controller developed in this research uses a marine boiler to illustrate the application. The successful development of flow control language by TOC in this research will enable academic research on PLC-derivative applications. The results of this research will help more SMEs to move into smart manufacturing and the new realm of Industry 4.0.

The efficiency of an industrial park’s operations is an indicator of how well the park can serve the companies located there. These supports include support for environmental water resources and business operations. In this study, a model for measuring water resources management efficiency is developed at the conceptual level using the management mindset of relative efficiency and management by objectives, and a modified Delphi method is used to determine the feasibility of a measurement model for water resources management efficiency. Furthermore, DEA data envelopment analysis was used to analyze the overall operational efficiency of the park. The results of the study showed that the model developed in this study for measuring water resources efficiency is of practical use. In addition, water resource management efficiency can be used as an indicator to assist in the determination of the operating efficiency of the industrial park when it is derived from the DEA analysis. In this study, among the 31 industrial parks in Taiwan, the operating efficiency values were classified into four categories, and the results show that the operating efficiency of most of the industrial parks need to be improved.