Decision Supporting Methodology and System Based on Theory of Constraints for Making an Optimal Product Portfolio Strategy in Shipbuilding Industry

Shipbuilding is a typical ‘build to order’ industry. It has a business model that generates revenues from building various ships and offshore products in accordance with owner’s requirements at each production stage. Under uncertainty in shipping market, it is very essential for the shipbuilder to prepare the fast and competitive decision for product portfolio strategy in order to maximize contribution margin by exploiting production facilities and constraints. TOC(theory of constrains) proposed by Dr. goldratt in 1979 has been evolved into a management philosophy with practices and principles spanning a multitude of operations management sub-disciplines.[1] In this study, we introduce the unique decision supporting methodology for the optimal product portfolio sets based on TOC. This methodology is established by adopting the concept of Drum Buffer Rope (DBR)[2] in constraints planning and Throughput Account (TA)[3][4][5] in management accounting of TOC. In addition, Decision Supporting System (DSS)[6] is implemented by applying this methodology. This DSS system provides a throughput estimator with reflecting the cost structure of shipbuilding industry and a resource simulator built on heuristic algorithms to operate major constraint-resources in shipyard such as dock, quay and pre-erection area etc. Several examples are presented to show that the proposed methodology and system can effectively support the strategic decision-making process of a global shipbuilding company

A Particle Dispersion Model For Analysis Of Two-Dimensional Mixing In Open Channels

Pollutant mixing in natural rivers is analyzed by using the two-dimensional depth-averaged advection-dispersion model (2D ADE) for rapid completion of the vertical mixing. The dispersion term in the 2D ADE follows Taylor’s assumption (Taylor, 1954; Fischer et al., 1979) which can be applied in the Taylor period. However, most open channel flow has long initial period which makes the skewed concentration distribution due to the unbalance between the shear flow advection and the vertical mixing (Chatwin, 1970). Therefore, the non-Fickian dispersion model is necessary to compensate the limitations of the 2D ADE model. In this research, the two-dimensional particle dispersion model (2D PDM) was developed to analyze the pollutant mixing both in the initial and the Taylor period without determination of the dispersion coefficient. In the 2D PDM, pollutant particles were introduced to visualize physical mixing process according to the complicate flow variation in open channels. The 2D PDM is based on the shear flow dispersion theory and adopted the operator split method which divides the shear advection stage and the turbulent diffusion stage. In the shear advection stage, particles were separated by the vertical velocity deviations in the longitudinal and transverse directions. The separated particles according to the shear flow were mixed across the vertical in the turbulent diffusion stage. After the particle mixing, the particle distribution in each time step was converted to the concentration field for various analysis. The 2D PDM was applied to the straight channel and the meandering channel for analysis of the conservative pollutant mixing. In the straight channel, concentration curves from the 2D PDM showed skewed distribution in the initial period and then turned into the Gaussian distribution in the Taylor period. And, the concentration distributions in the meandering channel showed good agreement with the tracer test results

Electrochemical CO₂ Reduction to CO Catalyzed by 2D Nanostructures

Electrochemical CO₂ reduction towards value-added chemical feedstocks has been extensively studied in recent years to resolve the energy and environmental problems. The practical application of electrochemical CO₂ reduction technology requires a cost-effective, highly efficient, and robust catalyst. To date, vigorous research have been carried out to increase the proficiency of electrocatalysts. In recent years, two-dimensional (2D) graphene and transition metal chalcogenides (TMCs) have displayed excellent activity towards CO₂ reduction. This review focuses on the recent progress of 2D graphene and TMCs for selective electrochemical CO₂ reduction into CO