The automotive industry is complex and global. An automotive supply chain involves multiple manufacturers and service providers in different parts of the chain across different countries. Diffusion of the global production system creates both opportunities and challenges for the supply chain itself as well as production base countries. Thailand is a production base for over 15 automotive brands. The industry contributes significantly to the Thai economy and employs approximately half a million people. To address competitiveness of the Thai automotive industry, its supply chain is studied in this paper. Ten factors affecting the competitiveness of the Thai automotive supply chain are analysed through the fuzzy DEMATEL method. The method forms a structural model that categorises the causal or effect roles of the factors, and the degree at which they impact the supply chain. This study focuses on Tier 1 and Tier 2 manufacturers of the supply chain. The results reveal that there are three common causal factors and four common effects in both tiers. The other four factors play different roles in different tiers. Managerial implications relating to these factors are also discussed and certain recommendations proposed in order to enhance the competitiveness of the Thai automotive supply chain.

This paper applied the optimization model of the biogas utilization pathway with the biogas utilization availability assessment to examine the effect of biogas system parameters on biogas utilization. The model analyzes the biogas utilization pathway availability and maximum profit to value added and productivity in biogas from industry wastewater in Thailand. The results showed that profit and availability of biogas utilization reduce biogas loss to flare, that it entails several conversion processes. The scenario for the biogas utilization pathway and storage with biogas production technology improves. Evaluated are operation time, waste and energy demand to the cassava starch usage during the production for 50–1000 tons per day. Five mature biogas production technologies were benchmarked evaluated based on the chemical oxygen demand removal efficiency and biogas yields. Subsequently, low-, medium-, and high-pressure storages and a battery storage were considered and discussed in this paper as suitable energy storage for each desired biogas plant operation. Five biogas utilization pathways, including converting biogas into thermal energy, generating electricity, and upgrading biogas to compressed biogas, were then compared. Those improved options in the scenario select suitable biogas technologies, storage, and application for value-added, reduce the environmental problems and renewable energy production from wastewater.

In this paper, a crop production schedule for a cooperative is determined considering a social objective of similar revenues for all smallholder farmer members. The problem involves multiple crops, multiple smallholder farmers, and multiple periods. The current planning is performed manually and results in haphazard amounts of revenue per farmer. A priority-based max-min heuristic (PMMH) is proposed to solve this problem. A social objective of the PMMH is to minimise the standard deviation of the revenue per greenhouse. The proposed heuristic reduces this standard deviation in the solution by reallocating crops among the greenhouses of the farmers, especially those farmers with very high or very low revenues. The PMMH is tested on various problem scenarios. The solutions obtained with the PMMH provide better objective function values than those from What’s Best solver. The results also show that the revenue per greenhouse is affected by the number of greenhouses per farmer.

In paper production, a jumbo reel is cut into multiple intermediate rolls, and each intermediate roll is then sheeted as finished goods. This problem is called a cutting stock problem and is proven to be NP-hard. The objective is to minimize material waste or trim loss from all the cuttings. In the case that any intermediate roll is not entirely used for its associated order, the intermediate roll itself could turn to be a dead stock. We use the concept of universal sizes of intermediate rolls to eliminate the dead stock. A pre-defined number of universal sizes of intermediate rolls is to be used to serve all the orders. The problem is solved using Reinforcement Artificial Bee Colony algorithm with Integer Linear Programming subroutine. This proposed approach is then tested with a set of 1,055 orders and 127 different sizes of sheet papers from a paper manufacturer. The results reveal that our method outperforms other algorithms. Our method offers the total trim loss of 3.51%, compared to the trim loss reported by the industry of at least 5%. This approach not only reduces the number of partially cut rolls, but also decreases the number of the jumbo reels needed to serve all the orders. Therefore, both the inventory cost and material cost can be saved.