Tactical project planning under uncertainty: fuzzy approach

At the tactical planning level in a multi-project environment, uncertainties are inherent to the workloads, and costs may be involved for using non-regular capacity and violating project due dates. We propose an approach to identify whether non-regular capacities might be needed to meet the projects' due dates. This problem is known as rough-cut capacity planning (RCCP) problem under uncertainty. We propose a possibilistic approach, which is based on modelling uncertain workloads with fuzzy sets. We present the resulting fuzzy rough-cut capacity planning (FRCCP), and show that we can use the possibilistic approach to provide a robust solution with a fuzzy resource loading profile that supports managers in decision making. We provide a simulated annealing approach to solve the FRCCP, and test it against several existing RCCP approaches. For the experiments we use real life instances from a shipyard maintenance centre

Escalonamento ótimo baseado na teoria de controle supervisório aplicado a um estaleiro de reparo naval

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-graduação em Engenharia de Automação e Sistemas, Florianópolis, 2010A Teoria de Controle Supervisório (TCS) permite a síntese automática de supervisores não bloqueantes que habilitem todas e apenas as sequências que satisfaçam especificações de segurança para um sistema a eventos discretos temporizado. O supervisor ótimo que satisfaz as especificações de recursos, roteiros e prazos para problema do tipo jobshop contém todas as soluções de escalonamento possíveis. No entanto, o crescimento do número de estados dos modelos pode inviabilizar a solução para problemas reais. Nessa pesquisa, uma nova proposta de modelagem dos autômatos temporizados é desenvolvida com o objetivo de reduzir o tamanho dos modelos. Propõe-se também um algoritmo eficiente para síntese de escalonamento baseada na composição incremental dos roteiros de produção e prazos das tarefas e um método de bissecção para minimização do tempo de produção global e também dos tempos de produção de cada tarefa. Este método é aplicado a um estaleiro de reparo naval para o escalonamento das atividades nos cinco recursos principais para execução de dez obras distintas. Também foi desenvolvido um sistema que integra o planejamento da produção com uma ferramenta de síntese automática de supervisores para que o usuário não precise estar familiarizado com a TCS.The Supervisory Control Theory (SCT) allows automatic synthesis of nonblocking supervisors that ensures safety specifications to a timed discrete event system. The optimal supervisory that ensures the resources specifications, production routers, and due dates to the problem of jobshops provides all the possible solutions of scheduling. However, the size of the state space of the models can make impracticable the solution of such a problem. In this dissertation, a new modeling approach is proposed for the timed automata models in order to expressively reduce the size of the models. Also, it is proposed an efficient algorithm for the optimal schedules based on an incremental synthesis of the production routers and due dates. A method of bisection was developed to minimize of total production time and the lead times of jobs as well. This method is applied to a repair shipyard to schedule its activities in the five main resources and ten orders. From the research was developed a system that integrates the production planning with a tool of automatic synthesis of supervisors in order to make the interface an easier place for those users who are not used to SCT

Optimal Ship Maintenance Scheduling Under Restricted Conditions and Constrained Resources

The research presented in this dissertation addresses the application of evolution algorithms, i.e. Genetic Algorithm (GA) and Differential Evolution algorithm (DE) to scheduling problems in the presence of restricted conditions and resource limitations. This research is motivated by the scheduling of engineering design tasks in shop scheduling problems and ship maintenance scheduling problems to minimize total completion time. The thesis consists of two major parts; the first corresponds to the first appended paper and deals with the computational complexity of mixed shop scheduling problems. A modified Genetic algorithm is proposed to solve the problem. Computational experiments, conducted to evaluate its performance against known optimal solutions for different sized problems, show its superiority in computation time and the high applicability in practical mixed shop scheduling problems. The second part considers the major theme in the second appended paper and is related to the ship maintenance scheduling problem and the extended research on the multi-mode resource-constrained ship scheduling problem. A heuristic Differential Evolution is developed and applied to solve these problems. A mathematical optimization model is also formulated for the multi-mode resource-constrained ship scheduling problem. Through the computed results, DE proves its effectiveness and efficiency in addressing both single and multi-objective ship maintenance scheduling problem

Pmi Methodology Utilization In Shipbuilding Project Management

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2012Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2012Bu çalışmada, PMI (Proje Yönetim Enstitüsü) tarafından verilen proje yönetim standardının, gemi inşaatı projelerindeki kullanımı, uygulanabilirliği ve faydası araştırılmıştır. Literatürde kısmi çalışmalar olmasına rağmen, sistematik bir proje yönetim metodolojisinin Türkiye’deki gemi inşaatı projelerine uygulanması ile ilgili bir çalışmaya rastlanamamıştır. Bu nedenle, uluslararası tanınırlığı olan bir proje yönetim standardının, gemi inşaatı projelerinde kullanımına ilişkin genel bir bakış verilmesi amaçlanmıştır. Bu araştırma, gemi inşaatı süreçleri ve uygulamaları konusunda uzmanlaşmış kişilerle yapılan birebir görüşmelere dayanmaktadır. Görüşmeler sırasında, PMI proje yönetim süreçleri ile ilgili kısa bilgilendirmelere yer verilmiş ve her bir sürecin gemi inşaatı projelerindeki kullanımına, uygulanabilirliğine ve faydasına ilişkin olarak uzmanların görüşleri alınmıştır. Çalışmanın sonucuna göre, PMI proje yönetim sürelerinin uygulanması, gemi inşaatı projelerinde fayda sağlayacaktır; ancak, tüm süreçlerin bir anda uygulanmaya başlanması, mevcut organizasyonların olgunluk seviyesi, eğitimli ve kalifiye personel eksikliği, kültürel sebepler ve değişken pazar şartları nedeniyle mümkün olamayacaktır.In this study, the utilization, practicality and usefulness of PMI (Project Management Institute) project management methodology, in shipbuilding project management is investigated. Although, some studies exist in the published literature related to managing specific processes or process groups of a shipbuilding project; a systematic project management methodology for shipbuilding in Turkey is not found. Therefore, in this study, it is aimed to give a brief overview on utilization of an internationally known project management standard in shipbuilding. The method of this study is based on interviews with shipbuilding experts. The project management standards are not well known or applied in Turkish shipbuilding industry. Therefore, the interviews cover a brief presentation of PMI project management standard and discussion over the utilization, practicality and usefulness of each process for shipbuilding projects in Turkey. Expert view is also investigated for the necessity of additional processes, process groups or knowledge areas other than the ones mentioned in PMI. In addition, the general comments from the experts are gathered related with the usual practices in Turkish shipbuilding projects. According to the study, most of the processed defined in PMI project management standard (PMBOK) were found to be useful if utilized. However, it would not be practical to start applying all processes at the same because of the maturity level of the organizations, availability of skilled and educated personnel, cultural reasons and changing market conditions.Yüksek LisansM.Sc

IIoT-Enabled Manufacturing Process Monitoring and Resource Positioning

Department of System Design and Control EngineeringScheduling and planning are the central functions to increase the productivity in manufacturing. In a shop floor, these functions should be deployed in a real-time manner by considering the dynamic conditions of manufacturing processes. In this regard, the prerequisite is seamless manufacturing process monitoring to acquire live workplace data. Manual data acquisition by experienced workers can provide a reliable process report at low cost. However, this may shoulder additional responsibilities of the current workload which can affect job performance in a negative way. Recently, industrial internet-of-things technology with advanced sensors and long-ranged telecommunication devices have enabled us to acquire high quality workplace data. Therefore, the objective of this study is to develop a manufacturing process monitoring system that provides two main functions: (i) a production progress monitoring and (ii) a manufacturing resource positioning. To do this, we first analyze a target manufacturing system and extract the key characteristics for production progress monitoring. We then discuss how to select the appropriate process data and determine the data acquisition method. Production progress is measured by comparing the acquired field data with the scheduled manufacturing plan. We estimate manufacturing resources positions and workspace by (i) analyzing the operation data of overhead cranes in a shipyard and (ii) interpreting correlation lags between acoustic signals obtained by multiple microphone sensors. The developed manufacturing process monitoring system is illustrated and demonstrated with the case study of ship block assembly monitoring.clos

Spatial Scheduling Algorithms for Production Planning Problems

Spatial resource allocation is an important consideration in shipbuilding and large-scale manufacturing industries. Spatial scheduling problems (SSP) involve the non-overlapping arrangement of jobs within a limited physical workspace such that some scheduling objective is optimized. Since jobs are heavy and occupy large areas, they cannot be moved once set up, requiring that the same contiguous units of space be assigned throughout the duration of their processing time. This adds an additional level of complexity to the general scheduling problem, due to which solving large instances of the problem becomes computationally intractable. The aim of this study is to gain a deeper understanding of the relationship between the spatial and temporal components of the problem. We exploit these acquired insights on problem characteristics to aid in devising solution procedures that perform well in practice. Much of the literature on SSP focuses on the objective of minimizing the makespan of the schedule. We concentrate our efforts towards the minimum sum of completion times objective and state several interesting results encountered in the pursuit of developing fast and reliable solution methods for this problem. Specifically, we develop mixed-integer programming models that identify groups of jobs (batches) that can be scheduled simultaneously. We identify scenarios where batching is useful and ones where batching jobs provides a solution with a worse objective function value. We present computational analysis on large instances and prove an approximation factor on the performance of this method, under certain conditions. We also provide greedy and list-scheduling heuristics for the problem and compare their objectives with the optimal solution. Based on the instances we tested for both batching and list-scheduling approaches, our assessment is that scheduling jobs similar in processing times within the same space yields good solutions. If processing times are sufficiently different, then grouping jobs together, although seemingly makes a more effective use of the space, does not necessarily result in a lower sum of completion times

Optimization of Continuous Maintenance Availability Scheduling

Every few months each United States submarine must return to a port to undergo major maintenance that cannot be conducted at sea. These maintenance periods are called Continuous Maintenance Availability (CMAV) periods. All CMAV scheduling aboard the two remaining submarine tenders in the United States fleet, the USS Emory S. Land (AS 39) and the USS Frank Cable (AS 40), is currently done manually. The schedulers rely on their experience and sound judgment with the goal of successfully completing the most maintenance as quickly and efficiently as possible for approximately 200 jobs, 50 maintenance shops and a host of other considerations. In this thesis, we develop a job-shop scheduling model, the CMAV Scheduler (CMAV-S). This is a large-scale, mixed-integer, linear program that accounts for a variety of scheduling inputs commonly used by planners: job priority, duration, allowed window of execution, prerequisites, mandatory character, workforce used and available (by shop), and special submarine conditions (active or inactive) needed to perform a job. CMAV-S produces near-optimal schedules that achieve maximum value for all scheduled jobs in about one minute. When compared to our own manual scheduling, we observe CMAV-S improves up to 25% the required CMAV length to schedule all maintenance.http://archive.org/details/optimizationofco1094543868Lieutenant, United States NavyApproved for public release; distribution is unlimited

Time compression in ETO production networks : A case study of Ulstein Shipyard

Confidential until 12 June 202

Development of Integrated Production Planning System for Shipbuilding and Application of Artificial Intelligence

학위논문(박사) -- 서울대학교대학원 : 공과대학 조선해양공학과, 2022.2. 우종훈.조선업은 대표적인 수주 산업으로 일정 수준의 수주 물량을 안정적으로 확보하는 것이 조선소 경영에서 가장 중요한 일이다. 2008년 글로벌 금융위기 이후 장기간 이어져오고 있는 조선업 불황의 상황에서 수주 선가의 개선은 이루어지지 않고 있으며, 한국 조선업은 일본, 중국과 치열한 수주 경쟁을 벌이고 있다. 수주 경쟁력 확보를 위해서는 우수한 성능의 선박을 개발하는 것과 함께 생산 원가 혁신이 필요하며, 이를 위해 정교한 생산계획 수립을 통해 선박의 생산 과정에서 발생할 수 있는 낭비 요소를 줄이는 것이 필수적이다. 정교한 생산계획 수립을 위해 생산계획 수립을 지원하는 생산계획 시스템의 고도화가 절실하다. 조선산업에서 생산계획 시스템의 개념은 1980년대 조선 CIM 구축과 함께 논의되었고, 1990년대 개인용 컴퓨터의 도입시기를 거쳐 2000년대 대형 조선소 중심으로 전사적 자원관리 시스템(ERP)의 도입에 맞추어 Advanced Planning 수립을 위한 생산계획 시스템이 구축되었다. 2000년대 이후 최적화 기법을 조선 생산계획에 적용하려는 시도가 있었고, 시뮬레이션 기법을 도입하여 디지털 조선소를 구축하는 등 생산계획 수립을 효율적으로 수행하고 최적의 생산계획 수립을 지원하려는 연구가 있었으나 생산계획 업무의 복잡성, 최적화 및 시뮬레이션 기술의 한계 등으로 실제 생산계획 업무에 적용된 사례는 부족하였다. 본 연구에서는 ERP도입에 맞추어 생산계획 업무를 전사적 프로세스 차원에서 분석 설계하고 체계적인 개발 방법론을 적용한 생산계획 시스템 구축의 사례를 소개한다. 시스템 구축과 함께 계획에 사용되는 표준 데이터를 정립하고 표준 코드를 정의하였다. 기존의 생산계획 시스템은 일부 계획자의 업무 필요성에 따라 제한적인 기능으로 개발되어 사용되어 왔으며, 계획 데이터는 전사 표준으로 사용되지 못하고 계획자의 필요에 따라 제한적으로 정의하여 사용하는 등 생산계획 업무가 전사적 차원의 업무 프로세스로 정의되지 못하였다. 본 연구의 사례를 통해 ERP와 연동 가능한 전사 프로세스에 통합된 생산계획 프로세스를 확립하였다. 또한, 최근 IT 기술의 발전과 인공지능 기술의 급격한 발전에 따라 최적화 및 인공지능 기술의 조선소 생산계획에 적용 가능성을 검토하였다. 조선소의 장기계획인 선표계획에 대해 Berth plan 수립에 제약만족기법을 적용하고, 공종별 부하 분석을 위해 지도학습(Supervised learning)을 통해 적절한 S-Curve를 제시할 수 있도록 하였다. 중기계획인 기준계획에 일반적으로 사용되는 Gantt planning에 대해서 강화학습(Reinforcement learning) 기술의 적용 가능성을 검토하였다. 기존의 일정계획 최적화 연구가 대부분 수리적 최적해를 찾기 위해 노력하였으나 문제의 크기가 너무 크고, 조선소 생산의 다양한 변수를 고려할 때 일부 변수를 고려한 최적해가 실제 조선 생산 전체에 대한 최적의 생산계획이 되기 어려운 점을 고려할 때 생산계획 수립 시 고려할 제약조건을 만족하는 적정한 케이스들을 도출하고, 생산계획 전문가가 도출된 케이스 중 가장 적합한 케이스를 선택할 수 있도록 지원하는 방식이 효과적일 수 있음을 사례 연구를 통해 확인하였다.The shipbuilding industry is a representative industry which produces on orders and securing a certain level of order volume is the most important thing in shipyard management. During the long-term depression in the shipbuilding industry since the 2008 global financial crisis, the shipbuilding industry has not improved its order prices, and the Korean shipbuilding industry is competing fiercely with Japan and China for orders. It is necessary to develop a ship with excellent performance and to innovate the production cost for the competitiveness of winning orders. There is an urgent need to upgrade the production planning system that supports making sophisticated production plans. In the shipbuilding industry, the concept of the production planning system was discussed along with the establishment of the shipbuilding CIM in the 1980s, followed by the introduction of personal computers in the 1990s. Production planning systems for making advanced planning had developed in line with the introduction of the enterprise resource planning system (ERP) mainly by large shipyards in the 2000s. Since the 2000s, there have been attempts to apply the optimization technique to shipbuilding production planning, and there have been studies to efficiently implement production planning and support making optimal production plans, such as introducing a simulation technique to build a digital shipyard. But, due to complexity of shipbuilding process, limitations of optimization and simulation technology, there were insufficient cases applied to actual production planning work. In this study, an example of developing the production planning system by analyzing and designing production planning tasks at the company-wide process level in line with the introduction of ERP and applying a systematic development methodology is introduced. Along with system construction, standard data used for planning was established and standard codes were defined. The existing production planning system has been developed and used with limited functions to meet the needs of some planners. Planning data was not used as a company-wide standard, and production planning tasks were not defined as a company-wide business process. Through the case study, a production planning process integrated into the enterprise process that can be operated in conjunction with ERP was established. In addition, with the recent development of IT technology and rapid development of artificial intelligence technology, the possibility of optimization and application of artificial intelligence technology to shipyard production plans was reviewed. The constraint satisfaction technique was applied to making the Berth plan for the long-term plan of the shipyard, and the appropriate S-Curve could be suggested through supervised learning for load analysis by work type. The applicability of reinforcement learning technology was reviewed for Gantt planning, which is generally used in master planning, which is a medium-term plan. Most of the existing schedule planning optimization studies have tried to find a mathematical optimal solution, but the size of the problem is too large, and when considering various variables in shipyard production, it is difficult for the optimal solution considering some variables to be the optimal production plan for the entire shipbuilding production. It was confirmed through case studies that it can be effective to derive appropriate cases that satisfy the constraints to be considered when making a production plan, and to support production planning experts to select the most suitable case among the derived cases.초록 i 목차 iii 1. 서론 1 1.1 연구 배경 1 1.2 조선산업의 특성 5 1.3 선행 연구 7 1.3.1 시대별 연구 흐름 7 1.3.2 분야별 연구 사례 19 1.4 연구 목적 31 1.5 논문의 구성 32 2. 조선소 생산계획 업무 프로세스 분석 및 고찰 34 2.1 선박건조 생산 단계 34 2.2 생산계획 단계 41 2.2.1 생산계획 단계 정의 44 2.2.2 선표계획 51 2.2.3 기준계획 58 3. 조선소 통합 생산계획 시스템 개발 71 3.1 개발 방법론 71 3.2 업무 프로세스 분석 73 3.2.1 As-Is 분석 73 3.2.2 To-Be 설계 78 3.3 시스템 아키텍처 설계 82 3.3.1 요구사항 분석 82 3.3.2 아키텍처 정의 89 3.3.3 시스템 설계 97 3.3.4 시스템 구현 100 3.4 개발 시스템의 적용 107 4. 생산계획 고도화를 위한 최적화 및 인공지능 적용 사례 연구 113 4.1 기존 생산계획 연구의 한계 113 4.1.1 생산계획 업무의 복잡성 115 4.1.2 최적화 및 시뮬레이션 기술의 한계 115 4.1.3 휴리스틱 의존 116 4.2 생산계획 프로세스와 최적화 및 인공지능 기술 117 4.3 장기계획을 위한 최적화 및 인공지능 기술 119 4.3.1 개요 119 4.3.2 적용 기술 소개 121 4.3.3 모델링 및 실험 124 4.3.4 분석 및 결론 142 4.4 중기계획을 위한 최적화 및 인공지능 기술 145 4.4.1 개요 145 4.4.2 강화학습 알고리즘 148 4.4.3 Environment 모델링 152 4.4.4 학습 케이스 157 4.4.5 테스트 164 5. 결론 168 참고문헌 170박