Shipping Modes Research Articles

Pharmaceutical Supply Chain Management

Supply chain management (SCM) refers to the coordination and oversight of all activities involved in the production, procurement, transformation, and delivery of goods or services from the point of origin to the point of consumption. It encompasses the planning, execution, and control of various processes involved in the flow of materials, information, and finances across the entire supply chain. In this paper, the authors have done a detailed analysis of the pharmaceutical dataset and predicted useful metrics that can be used in the shipping industry. This paper aims to demonstrate the application of machine learning models on the prediction of shipping mode. The model is trained on various features of the pharmaceutical supply chain dataset such as unit price, first-line designation, and delivery dates. Data cleaning and feature engineering were done and multiple models were trained. Out of the models tested, XGboost was found to give the best results for the prediction of weight, shipment modes and delivery date. Key Words: Supply chain management, Machine Learning models, Shipping Industry, XG Boost

The Effect of Packaging Types on Fresh Peaches in the Direct‐To‐Consumer Environment: Distribution Testing, Life Cycle Assessment and Economic Impact

ABSTRACTThe direct‐to‐consumer (D2C) shipping mode presents new opportunity for fresh peach sales in North America where demand over the past four decades has steadily declined. The hazards in this distribution mode are severe, and fresh peaches are fragile emphasizing the need for proper protection. A full analysis that not only encompasses the effects of the D2C distribution environment but also incorporates analyses of the environmental and economic impact of the packages utilized for transit of peaches is necessary. In this study, we use the metrics of peach grade, firmness, soluble solids concentration and percent softness before and after the distribution simulation to compare the protective performance of six DTC packaging systems. All six packages consist of a single layer corrugated box with varying primary packaging. A life cycle analysis of each package system is performed as well as an economic analysis on the packaged materials and cost to ship. We conclude that peach damage in shock testing is related to the freedom of movement that peaches have within each package type and varies by package system. All the package types evaluated amplify input vibration in the frequency range commonly associated with the input from the tires of truck‐trailer systems. There are no statistical differences between package systems in the distribution simulation of the six package types except in peach softness and grade of melting flesh peaches. Finally, we found that a reduction in material use and change in format, that is, foam sheets to foam netting, provides for sufficient peach protection while reducing environmental and economic impact.

Fault-tolerant controller based on artificial intelligence combined with terminal sliding mode and pre-described performance function applied on ship dynamic position stabilization systems

The presented study, develops an intelligent fault-tolerant controller to automatically control and maintain the position of a ship. The controller possesses the capabilities of holding the ship steady at a fixed position, automatically transferring the ship from one point to another, and tracking a target in the presence of various disturbances, uncertainties in the ship model, and thruster faults. A backstepping control approach based on the Terminal Sliding Mode method is employed to improve the accuracy of the controller. The aforesaid method guarantees time-limited convergence without relying on the initial conditions of system. A pre-described performance function (PPF) is utilized to ensure the performance in transient states and the calculations, which leads to the specific equations achievement for the study, which guarantees the system's stability. Environmental disturbances, uncertainties, and thruster faults are estimated using a Radial Basis Neural Network, allowing the controller to adapt to changes in the ship's environment and system uncertainties. The designed controller is proven to ensure the tracking error remains within a predefined range and can stabilize the ship system within a constant time without being influenced by the initial conditions. This stability is achieved in the presence of environmental disturbances, model uncertainties, and thruster faults, and the tracking error converges to a neighborhood near the origin. The controller is verified using a ship mode in the MATLAB environment, and the results show that the designed controller effectively controls the ship's position. The theoretical findings are successfully verified through these simulation tests.

Novel Shipping Modes and Inter-regional Transport Networks

Novel Shipping Modes and Inter-regional Transport Networks

A Region-wide Deployment of an Automated Real-time Truck Parking Availability Detection and Information Dissemination System

Commercial heavy vehicle-borne freight will continue to be the dominant cross-region shipping mode for materials and goods for the foreseeable future. Federal hours of service (HOS) regulations mandate scheduled minimum times for of-duty and in-transit rest periods to minimize operator fatigue. Without timely, accurate information disseminated to drivers and carriers on where to park, complying to HOS regulations can often become a very challenging task for drivers. This paper describes a region-wide deployment of a unique non-intrusive, multi-camera, truck parking space detection and availability information dissemination architecture. The architecture leverages multi-view Structure and Motion methods to reconstruct a Three-dimensional representation of the environment for estimating unoccupied spatial extents to deduce truck parking availability. Unlike 2D camera sensor-based methodologies, the advantage is its immediate adaptability to a variety of parking facilities and scenarios without the need for any subsequent re-training. The approach also mitigates errors arising from occlusions, and many other environmental conditions that confound many 2D camera-based approaches. The region-wide deployment, operated by a state transportation agency, has been online since early 2019, and has thus far substantiated the technical and day-to-day operational viability of the approach. The performance throughout this period indicates an overall accuracy at or above 90%. This paper provides a general overview of the deployed system architecture and performance characteristics across varied parking facility designs, parking behaviors, and other environmental conditions.

INVESTIGATING THE COST EFFECTIVENESS OF BIODIESEL DISTRIBUTION IN INDONESIA

The implementation of biodiesel in Indonesia has been regarded as one of the main strategies to improve country’s energy security equally and equitably. However, as the largest archipelago country in the world, the activity in distributing their biodiesel production bears a key problem. The complexity of delivering biodiesel from the supply point to the blending terminal of gasoil might result in cost inefficiency, which in turn will escalate the government funding of biodiesel incentives. This paper aims to both evaluate and formulate the Indonesian biodiesel transportation costs in all routes using either trucking or shipping mode. Based on primary data and information obtained from experts, we found that the most dominant factors that affect the shipping distribution cost are the size of the ship and its activities (such as voyage, ballast, loading, discharge, waiting, and buffer), whilst for the trucking mode, the dominant factors are both its corresponding operational costs and investment costs. Given that fuel prices fluctuate periodically, we also argue that the cost differences between the regulated and formulated reference may arise due to i) the data inaccuracy of the diesel fuel consumption and ii) specific terms outlined in the agreement between the corresponding transporters and suppliers.

Crowd-shipping as a Service: Game-based operating strategy design and analysis

Crowd-shipping as a Service (CSaaS), a novel concept proposed in this study for the Online-to-Offline (O2O) market, integrates different kinds of shipping services provided by individuals and public transport (PT) operators and enables booking and payment through a single CSaaS platform. It largely increases the shipping capacities and provides a flexible shipping mode for consignees with parcel delivery requests. Focusing on the role of the CSaaS platform, we design the commission-based and integrator-based operating strategies in the presence of CSaaS, where the CSaaS platform acts as an intermediary and a reseller, respectively. To explicitly depict the interactive relations among O2O players, i.e., the CSaaS platform, the individual-based crowd-shipping (I-CS) platform, the PT operator, the conventional logistics (CL) platform, and consignees, we adopt a game-theoretic approach to formulate the business models with and without CSaaS and derive the optimal behaviors of these players, i.e., the price decisions of platforms/operators and the choice decisions of consignees regarding which shipping mode (i.e., the I-CS, CSaaS, and CL modes) to choose. Analytical results show that the commission-based operating strategy outperforms the integrator-based strategy with a larger CSaaS platform's profit. In addition, the impact of CSaaS on O2O players is also identified by comparing the results of two business models, which is found to be closely related to the urban structure regarding PT accessibility. Managerial implications concerning launching the CSaaS service are proposed at last.

A Pilot Study of Stacked Autoencoders for Ship Mode Classification

With the evolution of the shipping market, artificial intelligence research using ship data is being actively conducted. Smart ships and reducing ship greenhouse gas emissions are among the most actively researched topics in the maritime transport industry. Owing to the massive advances in information and communications technology, the internet of things, and big data technologies, smart ships have emerged as a very promising proposition. Numerous methodologies and network architectures can smoothly collect data from ships that are currently in operation, as is currently done in research on reducing ship fuel consumption by deep learning or conventional methods. Many extensive studies of stacked autoencoders have been carried out in the past few years. However, prior studies have not addressed the development of algorithms or deep learning-based models to classify the operating states of ships. In this paper, we propose for the first time a deep learning-based stacked autoencoder model that can classify the operating state of a ship broadly into the categories of At Sea, Stand By, and In Port, using actual ship power load data. In order to maximize the model’s performance, the stacked autoencoder architecture, number of hidden layers, and number of neurons contained in each layer were measured by performance metrics such as true positive rate, false positive rate, Matthews correlation coefficient, and accuracy. It was found that the model’s performance was not always improved by increasing its complexity, so the feasibility of developing and utilizing an efficient model was verified by comparing it to real data. The best-performing model had a (5–128) structure with latent layer size 9. It achieved a true positive rate of 0.9035, a false positive rate of 0.0541, a Matthews correlation coefficient of 0.9054, and an accuracy of 0.9612, clearly demonstrating that deep learning can be used to analyze ship operating modes.

Exhaust emissions reduction and fuel consumption from the LNG energy system depending on the ship operating modes

In today’s environment of increasing pressure to reduce fuel consumption and emissions of carbon dioxide (CO2) and nitrogen oxides (NOx), the LNG (Liquefied Natural Gas) transportation industry is growing in size and influence. In this context, further efforts are needed to improve the energy efficiency of LNG marine energy power plant. The LNG vessels and their equipment considered in this study have different power consumption requirements depending on the vessel’s mode of operation (loading/unloading, maneuvering, anchoring, at sea, etc.). For each ship mode, where the power plant requirements are the same, the specific fuel consumption (SFOC) and exhaust emissions, NOx and CO2, are compared with a different number of engines in the network to find the optimal number of engines in the network, considering both the safety aspect and the port requirements. An analysis was performed showing the efficiency of the on-board power management system (PMS) in terms of manual load sharing between engines. A comprehensive analysis of the data and its comparison led to the conclusion that the manual distribution of power among the engines is the slightly better solution. The obtained results show that further analysis of the number of engines for a given load with minimum fuel consumption and CO2 and NOx emissions is required.

Reducing the carbon intensity of international shipping – The impact of energy efficiency measures

The International Maritime Organisation (IMO) has set a target to reduce the carbon intensity of shipping, or CO2 emissions per transport work, by at least 40% by 2030 from 2008 levels. While short-term measures which focus on improving energy efficiency have been implemented, their impact on carbon intensity trends of international shipping over time has not been quantified. This study quantifies and attributes the contribution of various driving factors to the overall change in carbon intensity of international shipping by ship type. The carbon intensity changes of each ship type are quantitatively linked to the overall carbon intensity target of the IMO. The study results highlight that reductions in carbon intensity at the ship-type and global level have been largely a result of decreases in energy intensity from 2012 to 2018 but reductions became smaller in the later period (2015–2018), underscoring the limits to energy efficiency measures. Furthermore, this study highlights the additional insights that can be drawn on the transport mode and freight activity profiles from the joint analysis of demand and supply-side indicators, revealing not only the changes in freight activity and capacity utilization, but also the shifts in capacity miles travelled for different shipping modes.

Experimental and Computational Fluid Dynamics Investigations into the Effect of Loading Condition on Resistance of Hard-Chine Semi Planning Crew Boat

Nowadays, the issue of energy efficiency in the maritime transportation sector has been strongly associated with the decreasing use of fossil energy and greenhouse gas emissions. Crew boats are one of the ship modes which consumes a lot of fuel in

GENERALIZED COST OF FREIGHT MULTIMODAL SYSTEM IN JAVA

The multimodal system in Indonesia requires development in order to create a more efficient and reliable freight transport and diminish the domination of road transport, i.e. trucks. The utilization of more than one mode in a multimodal system, where there is a door-to-door element, requires a network development concept that refers to the use of generalized costs, instead of costs incurred to use the system (out of pocket). Generalized cost is the concept of monetization of time, distance and cost variables into a certain unit value (time or cost). The aim of this study is to analyze the generalized cost model of freight transport in Java based on truck, train and ship modes. In this paper, the generalized cost variable used is based on the viewpoint from freight forwarders and shippers obtained through primary surveys and the AHP method cost, reliability and lead time. Monetization of reliability and lead time variables on costs is based on a stated preference survey, the results of which show that the truck mode has a time VOR Rp 1,181,771 and VOT Rp 174,079 (per delivery per hour). These values are the largest compared to the other modes considering that congestion and the unavailability of adequate infrastructure are the factors that cause delays. The results of the generalized cost show that the ship mode, which has the largest generalized cost value, is 1.29 times more expensive than the truck mode considering that the journey is heavily influenced by weather and has a need for further modes to the destination as well as additional handling equipment which increases transportation costs. The outcome are expected to be used by the government as a reference in determining multimodal transport development policies which will enable the system to compete in the logistics sector.

Emissions assessment of bulk carriers in China's east Coast-Yangtze River maritime network based on different shipping modes

In the past decades, resources such as iron ore were transported to the upper-middle reaches of the Yangtze River by river-sea combined mode in order to support the rapid economic development of Yangtze River Economic Zone. However, emissions from vessels have caused serious negative effect on the environment along the Yangtze River. Therefore, the Chinese government took a series of measures so as to control the emissions in this area. This paper draws comparisons among river-sea combined mode, river-sea mode and mixed mode (combination of the river-sea combined mode and river-sea mode) based on the ship emissions inventory of SOx, PM10, PM2.5, NOx, CO, HC, CO2, N2O and CH4 for 13 common cases in the existing network by bottom-up method. In addition, the paper carries out in-depth analyses, providing evidence for future ship operation directions. The results indicate river-sea mode and mixed mode which implement river-sea vessels record less unit emissions compared to the traditional river-sea combined mode. Moreover, shorter transshipment (lightning) times, proper ports of transshipping and cleaner fuels are able to reduce ship emissions significantly. Hence, we conclude that first, river-sea vessels should be encouraged; second, the initiative of a deep-water channel of the Yangtze River should be continued; and last, stricter regulations of fuels have played a significant role in reducing ship emissions.

Delay Prediction to Mitigate E-commerce Supplier Disruptions using Voting Mechanism

COVID-19 has severely affected supply chains and last-mile logistics. With a remarkable expansion in the internet-based deals of B2C online business and changed customer behaviors, it is critical to estimate delays with sufficient precision to avoid time-related uncertainty. The risk of a supplier's delivery being late will harm businesses' ability to fulfill client orders. Shipment information of an online business organization is utilized for the investigation. The dataset is pre-processed and important features are extracted using the Random Forest technique. We propose an enhanced hybrid voting-based classification model with Trees, and Ensemble techniques (like bagging and boosting) enabled by parameters like shipping mode, scheduled shipment time, and order type to anticipate the postponement with the highest accuracy. Since the base classifiers in the voting mechanism cannot perform at the same level, we assigned various weights and noticed a significant improvement in classification performance. Consistently, the proposed model depicts improved performance and provides strategic, operational, and industrial insights for decision-making in last-mile businesses.

Profitability of container shipping via the Arctic Northeast Passage: A simulation and regression analysis

The progressive retreat of Arctic sea ice in recent years has offered unprecedented opportunities for commercial shipping via Arctic shipping routes. However, actual annual transits via the Arctic Northeast Passage (NEP) are rare which signals that shipping companies are reluctant to use the NEP from a cost-benefit perspective. This paper analyzes the profitability of container shipping via the NEP. Based on observational data the distribution of profit for a single-voyage along the NEP for different ice class ships (Arc4 and Arc7) in different shipping modes (direct mode and transshipment mode) is generated via Monte Carlo simulations. The simulated data are then used in a seemingly unrelated regression analysis and in cross-equation testing to investigate the relative impact of various revenue and cost factors on the profit of container shipping via the NEP for the different shipping modes and ice ship classes. The study finds that the impacts of the various cost factors considered in the analysis indeed differ greatly across different shipping modes and different ice classes of container ships. The direct mode has a greater profit space than the transshipment mode and the Arc4 class ship has higher profitability than the Arc7 class ship under reasonable assumptions. Moreover, when the container freight rate of the NEP increases by 60% on basis of that of the traditional routes, shipping via the NEP will be profitable.

PERBANDINGAN KAPAL MONOHULL, CATAMARAN, TRIMARAN BERDASARKAN TINJAUAN OPERASIONAL PENGGUNAAN BAHAN BAKAR

In general, fishing fleets operating in Maluku waters and managed by local entrepreneurs consist of monohull and trimaran fishing vessels with outriggers. Monohull fishing vessels have limited deck space and poor transverse stability, while trimaran-type vessels have better deck space and transverse stability than monohull vessels, but because they are still in the form of outriggers, the space is limited. This study aims to examine the development of the trimaran fishing vessel in terms of energy requirements, safety, and comfort of the crew during fishing operations. The initial stage of this research begins with data analysis and the basic size of monohull fishing vessels operating in Maluku waters, from this data the shape of the trimaran hull is designed. Calculation of resistance using CFD, then analyzed the calculation of resistance and stability, safety, and comfort of the ship using Maxsurf. The drag Trimaran is 8.86% smaller than a monohull and 3.25% smaller than a catamaran. Energy Usage (EHP) is proven by trimaran ships more than other ship modes. The average trimaran period is 10.5 seconds which meets IMO standards and is declared operationally good.

Integrated production and transportation scheduling with order-dependent inventory holding costs

In this study, we consider an integrated production and transportation scheduling problem faced by make-to-order manufacturers that adopt a commit-to-delivery business mode and cooperate with third-party logistics providers to deliver processed products to customers. The third-party logistics providers typically offer multiple shipping modes chosen by the manufacturers to deliver products, each shipping mode with a shipping time guarantee and a shipping cost function that is non-increasing in shipping time and sub-additive, non-decreasing in shipping quantity. The problem involves inventory holding costs which not only depend on the time that the products spend in temporary storage but also depend on customer types. The problem is to determine an integrated production and shipping schedule that satisfies the committed delivery due date limitations for the customers, such that the total cost of shipping and inventory holding is minimized. We investigate two cases with and without split delivery. For both cases, we first show that both of them are ordinarily NP-hard, prove that there exist no polynomial-time approximation algorithms with constant worst-case ratios, propose exact algorithms to solve them, and finally design column generation-based heuristic algorithms to find feasible solutions. The computational results demonstrate that the heuristic algorithms are capable of generating near-optimal solutions efficiently. We also consider two interesting practical variants of the problem.

A Simulation-based Optimization Approach to Logistic and Supply Chain Network Design

The Department of Defense (DoD) operates a world-wide supply chain, which in 2017 contained nearly 5 million items collectively valued at over $90 billion. Since at least 1990, designing and operating this supply chain, and adapting it to ever-changing military requirements, are highly complex and tightly coupled problems, which the highest levels of DoD recognize as weaknesses. Military supply chains face a wide range of challenges. Decisions made at the operational and tactical levels of logistics can alter the effectiveness of decisions made at the strategic level. Decisions must be made with incomplete information. As a result, practical solutions must simultaneously incorporate decisions made at all levels as well as take into account the uncertainty faced by the logistician. The design of modern military supply chains, particularly for large networks where many values are not known precisely, is recognized as too complex for many techniques found in the academic literature. Much of the literature in supply chain network design makes simplifying assumptions, such as constant per-unit transportation costs regardless of the size of the shipment, the shipping mode selected, the time available for the delivery, or the route taken. This article avoids these assumptions to provide an approach the practitioner can use when designing and adapting supply chain networks. This research proposes a simulation-based optimization approach to find a near-optimal solution to a large supply chain network design problem of the scale faced by a theater commander, while recognizing the complexity and uncertainty that the practicing military logistician must deal with.

Bridge mechanical thrombectomy may be a better choice for acute large vessel occlusions.

Direct mechanical thrombectomy (DMT) was confirmed non-inferior to bridge mechanical thrombectomy (BMT, MT preceded by intravenous alteplase within 4.5h after symptom onset) for acute ischemic stroke with large vessel occlusions (AIS-LVO) in mothership patients. However, the noninferiority of DMT in the general population (including drip and ship mode) is controversial, and the impact of thrombolysis on retrieval attempts remains uncertain. This was a post-hoc analysis of a multi-center, prospective enrolled study. Patients were divided into the BMT group and the DMT group. Baseline characteristics and clinical outcomes were compared by using univariate analysis, multivariable analysis, and propensity score matching analysis, respectively. Of all 245 patients enrolled in this study, 79 (32.2%) patients underwent BMT. In the multivariable analysis, the ratio of excellent prognosis (defined as modified Rankin Scale [mRS] score 0-1 at 90days) was significantly higher in the BMT group compared with the DMT group (odds ratio, 2.731; 95% confidence interval, 1.238-6.023; P = 0.013). The ratio of good prognosis (mRS score 0-2 at 90days), successful recanalization rate [modified Thrombolysis In Cerebral Ischemia (mTICI) score 2b-3] and mortality rate were similar between the two groups. The excellent prognosis rate was significantly higher in the BMT group after propensity score matching (P = 0.023). BMT was associated with a higher ratio of excellent prognosis (mRS 0-1) and a similar successful recanalization rate without increasing peri-operation complications compared with DMT in AIS-LVO patients. It is prudent to continue BMT until further data is available.

Cold chain shipping mode choice with environmental and financial perspectives

Mode choice between reefer bulk and container in seaborne cold chains for time sensitive products is a practical problem, in which limited studies are available to guide decision makers. This study thoroughly investigates the cold chain mode choice problem by selecting shipping mode (containerized transport and bulk transport) for each shipment and determining shipment quantities and ship deployment in a multi-period planning environment with independent perishable product demands. Value-Based Management as a novel method in shipping is adopted to consider both economic and environmental objectives from operational and financial aspects. The value-based mode selection models also determine the sailing speed of the heterogeneous chartered reefer bulk fleet under different chartering terms. Furthermore, the paper evaluates greenhouse gas emissions from the cold chain shipping. Findings from a numerical example show that optimal ship speed decreases with a reducing rate when the bunker price increases and with a higher decline rate when goods are less perishable.