JC
J.M.G. Coenen
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8 records found
1
As an ever-increasing volume of data gets collected within industrial companies, existing data visualization methods become inadequate, and much of this data ends up just filling storage inside databases. This is particularly the case when interpreting data on the location of different resources, such as parts or machines, as it is difficult to represent intuitively with common options like tables or graphs. This paper explores how to effectively visualize this data and provide a solution that facilitates gaining visibility into lost items, production routes, and congestion. Specifically, a digital shadow dashboard is developed that maps production and resource data onto manufacturing companies’ floorplans. In addition, dynamic value stream mapping is also explored. Testing is done with industrial small-to-medium enterprises (SMEs), prioritizing low-cost software to ensure viability for them. A research through design approach is used to investigate the information needs of the SMEs, and to develop dashboard designs to address them. As a result, this project sits at a nexus between industrial engineering, UI/UX design, user research within industrial SMEs, and software prototyping on a low development budget. The contribution of the paper is the structured development of a digital shadow of factories’ floorplans, with a dashboard to convey part location data to users. The approach and steps taken also serve as a guide for the development of future digital shadow dashboards for industrial SMEs or research.
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As an ever-increasing volume of data gets collected within industrial companies, existing data visualization methods become inadequate, and much of this data ends up just filling storage inside databases. This is particularly the case when interpreting data on the location of different resources, such as parts or machines, as it is difficult to represent intuitively with common options like tables or graphs. This paper explores how to effectively visualize this data and provide a solution that facilitates gaining visibility into lost items, production routes, and congestion. Specifically, a digital shadow dashboard is developed that maps production and resource data onto manufacturing companies’ floorplans. In addition, dynamic value stream mapping is also explored. Testing is done with industrial small-to-medium enterprises (SMEs), prioritizing low-cost software to ensure viability for them. A research through design approach is used to investigate the information needs of the SMEs, and to develop dashboard designs to address them. As a result, this project sits at a nexus between industrial engineering, UI/UX design, user research within industrial SMEs, and software prototyping on a low development budget. The contribution of the paper is the structured development of a digital shadow of factories’ floorplans, with a dashboard to convey part location data to users. The approach and steps taken also serve as a guide for the development of future digital shadow dashboards for industrial SMEs or research.
Correct and accurate cost estimations are critical for shipyard companies. Traditionally cost estimations for one-off ship designs are based on expert opinions and statistical-based methods. In this paper, we introduce a method for improving cost estimations in the pre-contract stage of a one-off design shipbuilding project. Pre-contract means that the available information is limited. The introduced method is based on the idea that, although a new vessel has never been built before, cost of similar building assemblies can be found in the production information of earlier produced vessels. The assessment of similarities is performed by means of error-tolerant graph matching. Research to date shows that only taking the basic activities into account, without taking the context into account, does not always lead to a good and reliable result. The example in this paper is based on the ship block assembly process.
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Correct and accurate cost estimations are critical for shipyard companies. Traditionally cost estimations for one-off ship designs are based on expert opinions and statistical-based methods. In this paper, we introduce a method for improving cost estimations in the pre-contract stage of a one-off design shipbuilding project. Pre-contract means that the available information is limited. The introduced method is based on the idea that, although a new vessel has never been built before, cost of similar building assemblies can be found in the production information of earlier produced vessels. The assessment of similarities is performed by means of error-tolerant graph matching. Research to date shows that only taking the basic activities into account, without taking the context into account, does not always lead to a good and reliable result. The example in this paper is based on the ship block assembly process.
A method to quantify manufacturing activities for shipbuilding projects is devised, based on extrapolation of historical projects. Extrapolation rules are based on first principles and fine-tuned using empirical data. A 4-tier hierarchical system structure is proposed, incorporating different types of interrelations. Subsequently, it is investigated how design principles can be used to mathematically define these relations, resulting in a substantiated work content estimation model. Several shipbuilding projects, some of which recently executed, were used as data source to support the proposed theory.
It is demonstrated that detailed production man hour estimations can be made using limited sets of input data.
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A method to quantify manufacturing activities for shipbuilding projects is devised, based on extrapolation of historical projects. Extrapolation rules are based on first principles and fine-tuned using empirical data. A 4-tier hierarchical system structure is proposed, incorporating different types of interrelations. Subsequently, it is investigated how design principles can be used to mathematically define these relations, resulting in a substantiated work content estimation model. Several shipbuilding projects, some of which recently executed, were used as data source to support the proposed theory.
It is demonstrated that detailed production man hour estimations can be made using limited sets of input data.
Automatic planning literature for shipbuilding has historically only addressed the hull-related production processes, such as section building and erection. However, the outfitting process has become increasingly important for shipyards building complex ships. Rose et al. [1] developed a method for automatically generating a detailed outfitting planning, but never test the method's feasibility on a complete complex ship. This paper presents a test case of a pipelaying ship where this planning method produced a high quality outfitting planning. Furthermore, the method also allows shipyards to quantitatively assess outfitting-related strategic decisions. This paper uses the developed method to determine the impact of implementing multi-skilled mounting teams on the outfitting process. This analysis found that such teams can improve the flexibility of workforce allocation, but have little effect on the required movement of mounting teams between work-sites.
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Automatic planning literature for shipbuilding has historically only addressed the hull-related production processes, such as section building and erection. However, the outfitting process has become increasingly important for shipyards building complex ships. Rose et al. [1] developed a method for automatically generating a detailed outfitting planning, but never test the method's feasibility on a complete complex ship. This paper presents a test case of a pipelaying ship where this planning method produced a high quality outfitting planning. Furthermore, the method also allows shipyards to quantitatively assess outfitting-related strategic decisions. This paper uses the developed method to determine the impact of implementing multi-skilled mounting teams on the outfitting process. This analysis found that such teams can improve the flexibility of workforce allocation, but have little effect on the required movement of mounting teams between work-sites.
Efficient planning of the section building process is important for European shipyards since delays in this process can disrupt the on-time delivery of a ship. Automatically generating production schedules of the section building process can result in higher quality schedules compared to those created manually. Recently, the production processes of European shipyards have shifted to focus heavily on outsourcing and outfitting, yet existing automatic planning methods for section building fail to sufficiently consider these factors. This paper develops a mathematical model of the section building process which includes the effects of outfitting and outsourcing. The objective of this model is to simultaneously minimise the fluctuations in workload and the number of outsourced man-hours. The mathematical model was solved by implementing the non-dominated sorting generic algorithm-II (NSGA-II) using a custom heuristic as the fitness function. Due to the multi-objective nature of the problem definition and solution approach, a Pareto front of optimal solutions is created instead of a single, best solution. A test case showed that gains in both objectives are achievable compared to the planning developed manually. Implementing the Section Building Planning methodology developed in this paper could potentially improve the efficiency and controllability of the overall shipbuilding process.
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Efficient planning of the section building process is important for European shipyards since delays in this process can disrupt the on-time delivery of a ship. Automatically generating production schedules of the section building process can result in higher quality schedules compared to those created manually. Recently, the production processes of European shipyards have shifted to focus heavily on outsourcing and outfitting, yet existing automatic planning methods for section building fail to sufficiently consider these factors. This paper develops a mathematical model of the section building process which includes the effects of outfitting and outsourcing. The objective of this model is to simultaneously minimise the fluctuations in workload and the number of outsourced man-hours. The mathematical model was solved by implementing the non-dominated sorting generic algorithm-II (NSGA-II) using a custom heuristic as the fitness function. Due to the multi-objective nature of the problem definition and solution approach, a Pareto front of optimal solutions is created instead of a single, best solution. A test case showed that gains in both objectives are achievable compared to the planning developed manually. Implementing the Section Building Planning methodology developed in this paper could potentially improve the efficiency and controllability of the overall shipbuilding process.
Purpose
The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex ship types.
Design/methodology/approach
A bi-objective mathematical model is developed based on the process constraints. A Pareto front of possible erection schedules is created using a the Non-dominated Sorting Genetic Algorithm II with a custom heuristic fitness function and constraint violation.
Findings
It was possible to consistently generate a wide variety of production schedules with superior performance to those manually created by shipyard planner in negligible computational time.
Practical implications
The set of optimized production schedules generated by the developed methodology can be used as a starting point by existing shipyard planners when drafting the initial erection planning for a new project. This allows the planners to consider wider variety of options in less time.
Originality/value
No other published approach for the automatic generation of optimized production schedules of the erection process is specifically tailored to the construction of complex ships.
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Purpose
The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex ship types.
Design/methodology/approach
A bi-objective mathematical model is developed based on the process constraints. A Pareto front of possible erection schedules is created using a the Non-dominated Sorting Genetic Algorithm II with a custom heuristic fitness function and constraint violation.
Findings
It was possible to consistently generate a wide variety of production schedules with superior performance to those manually created by shipyard planner in negligible computational time.
Practical implications
The set of optimized production schedules generated by the developed methodology can be used as a starting point by existing shipyard planners when drafting the initial erection planning for a new project. This allows the planners to consider wider variety of options in less time.
Originality/value
No other published approach for the automatic generation of optimized production schedules of the erection process is specifically tailored to the construction of complex ships.
This paper explorers the possibilities to design a ship for a future 'sea change' like a major retrofit of the engine room. In order to assess the potential future beneficial impact of such design measures, a demonstrator method has been developed that scores a concept design for its 'Retrofit-penalty', thus allowing for comparison of design alternatives and what-if analyses in a very early stage. The conclusion is that such an approach is feasible, but in order to get more meaningful results further research on scaling of parameters is required.
...
This paper explorers the possibilities to design a ship for a future 'sea change' like a major retrofit of the engine room. In order to assess the potential future beneficial impact of such design measures, a demonstrator method has been developed that scores a concept design for its 'Retrofit-penalty', thus allowing for comparison of design alternatives and what-if analyses in a very early stage. The conclusion is that such an approach is feasible, but in order to get more meaningful results further research on scaling of parameters is required.