Assembly sequence planning using hybrid binary particle swarm optimization

Assembly Sequence Planning (ASP) is known as a large-scale, timeconsuming combinatorial problem. Therefore time is the main factor in production planning. Recently, ASP in production planning had been studied widely especially to minimize the time and consequently reduce the cost. The first objective of this research is to formulate and analyse a mathematical model of the ASP problem. The second objective is to minimize the time of the ASP problem and hence reduce the product cost. A case study of a product consists of 19 components have been used in this research, and the fitness function of the problem had been calculated using Binary Particle Swarm Optimization (BPSO), and hybrid algorithm of BPSO and Differential Evolution (DE). The novel algorithm of BPSODE has been assessed with performance-evaluated criteria (performance measure). The algorithm has been validated using 8 comprehensive benchmark problems from the literature. The results show that the BPSO algorithm has an improved performance and can reduce further the time of assembly of the 19 parts of the ASP compared to the Simulated Annealing and Genetic Algorithm. The novel hybrid BPSODE algorithm shows a superior performance when assessed via performance-evaluated criteria compared to BPSO. The BPSODE algorithm also demonstrated a good generation of the recorded optimal value for the 8 standard benchmark problems

An approach to evaluate the impact of the introduction of a disassembly line in traditional manufacturing systems

Purpose: The circular economy (CE) paradigm, traditionally based on the 3R (reuse, recycle, and remanufacture) principles, provides benefits for sustainability and represents a big opportunity for manufacturing enterprises to reduce costs and take economic advantages. This paper proposes an approach that can help stakeholders transition towards CE oriented business by evaluating the economic convenience of introducing a manual disassembly line to recover the components of End-of-Life (EoL) products in a traditional manufacturing system. Design/methodology/approach: The conceptual approach is generic and based on the characteristics of EoL products and on the reusability and recyclability features of every component. Then, based on the type of product and the disassembly sequence, the disassembly line is built in the virtual environment along the assembly line. The virtual environment must take into account the probabilistic parameters that characterise each real industrial context. Therefore, the assembly-disassembly lines are linked with the variables and economic functions needed to process the outputs of the approach application. Findings: Implemented in a virtual environment, the proposed approach evaluates a priori possible economic and environmental benefits coming from the integration of a disassembly line within a manufacturing context. The approach considers the variability of the EoL products’ status (their reusability and recyclability indices), provides the optimal number of operators that must be assigned to the manual disassembly line and determines the maximum reduction of the product cost that can be gained by introducing the disassembly line. Furthermore, an application example is provided to show the potential of the tool. Originality/value: Recently, the scientific literature has dealt with the issue related to the disassembly process of EoL products from several perspectives (e.g. disassembly line scheduling, planning, balancing, with and without the consideration of the quality of EoL products). However, to the best of our knowledge, no study provided an approach to evaluate the convenience of the investment in a disassembly line. Therefore, this document contributes to this research field by proposing a simple approach that supports the decision-making process of traditional manufacturing enterprises to evaluate a priori the economic return (i.e. how much the product cost decreases) and provide an estimate of the environmental benefits of integrating a manual disassembly line of EoL products with a traditional manufacturing systemPeer Reviewe

Adaptive genetic algorithm based on fuzzy reasoning for the multilevel capacitated lot-sizing problem with energy consumption in synchronizer production

The multilevel capacitated lot-sizing problem (MLCLSP) is a vital theoretical problem of production planning in discrete manufacturing. An improved algorithm based on the genetic algorithm (GA) is proposed to solve the MLCLSP. Based on the solution results, the distribution of energy consumption in a synchronous production case is analyzed. In the related literature, the GA has become a much-discussed topic in solving these kinds of problems. Although the standard GA can make up for the defects of the traditional algorithm, it will lead to the problems of unstable solution results and easy local convergence. For these reasons, this research presents an adaptive genetic algorithm based on fuzzy theory (fuzzy-GA) to solve the MLCLSP. Firstly, the solving process of the MLCLSP with the fuzzy-GA is described in detail, where algorithms for key technologies such as the capacity constraint algorithm and the algorithm of solving fitness value are developed. Secondly, the auto-encoding of decision variables for MLCLSPs is studied; within this, the decision variables of whether to produce or not are encoded into a hierarchical structure based on the bill of material; combined with external demand, the decision variables of lot-sizing are constructed. Thirdly, the adaptive optimization process of parameters of the GA for the MLCLSP based on fuzzy theory is expounded, in which membership function, fuzzy rule, and defuzzification of the MLCLSP is mainly presented. Experimental studies using the processed dataset collected from a synchronizer manufacturer have demonstrated the merits of the proposed approach, in which the energy consumption distribution of the optimized production plan is given. The optimal lot-sizing is closer to the average value of the optimal value compared with the standard GA, which indicates that the proposed fuzzy-GA approach has better convergence and stability

A Novel Assembly Line Scheduling Algorithm Based on CE-PSO

With the widespread application of assembly line in enterprises, assembly line scheduling is an important problem in the production since it directly affects the productivity of the whole manufacturing system. The mathematical model of assembly line scheduling problem is put forward and key data are confirmed. A double objective optimization model based on equipment utilization and delivery time loss is built, and optimization solution strategy is described. Based on the idea of solution strategy, assembly line scheduling algorithm based on CE-PSO is proposed to overcome the shortcomings of the standard PSO. Through the simulation experiments of two examples, the validity of the assembly line scheduling algorithm based on CE-PSO is proved

Direct modeling techniques in the conceptual design stage in immersive environments for DfA&D

Due to the fast – growing competition of the mass – products markets, companies are looking for new technologies to maximize productivity and minimize time and costs. In the perspective of Computer Aided Process Planning (CAPP), companies want to optimize fixture design and assembly planning for different goals. To meet these demands, the designers' interest in Design for Assembly and Disassembly is growing considerably and is increasingly being integrated into the CAPP. The work described in this thesis aims to exploit immersive technologies to support the design of mating elements and assembly / disassembly, by developing a data exchange flow between the immersive environment and the modeling environment that provides the high – level modeling rules, both for modeling features and for assembly relationships. The main objective of the research is to develop the capability to model and execute simple coupling commands in a virtual environment by using fast direct modeling commands. With this tool the designer can model the coupling elements, position them and modify their layout. Thanks to the physical engine embedded in the scene editor software, it is possible to take into consideration physical laws such as gravity and collision between elements. A library of predefined assembly features has been developed through the use of an external modeling engine and put into communication with the immersive interaction environment. Subsequently, the research involved the study of immersive technologies for workforce development and training of workers. The research on immersive training involved industrial case studies, such as the projection of the disassembly sequence of an industrial product on a head mounted display, and less industrial case studies, such as the manual skills development of carpenters for AEC sectors and the surgeon training in the pre – operative planning in medical field

Energy Efficient Policies, Scheduling, and Design for Sustainable Manufacturing Systems

Climate mitigation, more stringent regulations, rising energy costs, and sustainable manufacturing are pushing researchers to focus on energy efficiency, energy flexibility, and implementation of renewable energy sources in manufacturing systems. This thesis aims to analyze the main works proposed regarding these hot topics, and to fill the gaps in the literature. First, a detailed literature review is proposed. Works regarding energy efficiency in different manufacturing levels, in the assembly line, energy saving policies, and the implementation of renewable energy sources are analyzed. Then, trying to fill the gaps in the literature, different topics are analyzed more in depth. In the single machine context, a mathematical model aiming to align the manufacturing power required to a renewable energy supply in order to obtain the maximum profit is developed. The model is applied to a single work center powered by the electric grid and by a photovoltaic system; afterwards, energy storage is also added to the power system. Analyzing the job shop context, switch off policies implementing workload approach and scheduling considering variable speed of the machines and power constraints are proposed. The direct and indirect workloads of the machines are considered to support the switch on/off decisions. A simulation model is developed to test the proposed policies compared to others presented in the literature. Regarding the job shop scheduling, a fixed and variable power constraints are considered, assuming the minimization of the makespan as the objective function. Studying the factory level, a mathematical model to design a flow line considering the possibility of using switch-off policies is developed. The design model for production lines includes a targeted imbalance among the workstations to allow for defined idle time. Finally, the main findings, results, and the future directions and challenges are presented

De novo characterization of the gametophyte transcriptome in bracken fern, Pteridium aquilinum

<p>Abstract</p> <p>Background</p> <p>Because of their phylogenetic position and unique characteristics of their biology and life cycle, ferns represent an important lineage for studying the evolution of land plants. Large and complex genomes in ferns combined with the absence of economically important species have been a barrier to the development of genomic resources. However, high throughput sequencing technologies are now being widely applied to non-model species. We leveraged the Roche 454 GS-FLX Titanium pyrosequencing platform in sequencing the gametophyte transcriptome of bracken fern (<it>Pteridium aquilinum</it>) to develop genomic resources for evolutionary studies.</p> <p>Results</p> <p>681,722 quality and adapter trimmed reads totaling 254 Mbp were assembled <it>de novo </it>into 56,256 unique sequences (i.e. unigenes) with a mean length of 547.2 bp and a total assembly size of 30.8 Mbp with an average read-depth coverage of 7.0×. We estimate that 87% of the complete transcriptome has been sequenced and that all transcripts have been tagged. 61.8% of the unigenes had blastx hits in the NCBI nr protein database, representing 22,596 unique best hits. The longest open reading frame in 52.2% of the unigenes had positive domain matches in InterProScan searches. We assigned 46.2% of the unigenes with a GO functional annotation and 16.0% with an enzyme code annotation. Enzyme codes were used to retrieve and color KEGG pathway maps. A comparative genomics approach revealed a substantial proportion of genes expressed in bracken gametophytes to be shared across the genomes of <it>Arabidopsis</it>, <it>Selaginella </it>and <it>Physcomitrella</it>, and identified a substantial number of potentially novel fern genes. By comparing the list of <it>Arabidopsis </it>genes identified by blast with a list of gametophyte-specific <it>Arabidopsis </it>genes taken from the literature, we identified a set of potentially conserved gametophyte specific genes. We screened unigenes for repetitive sequences to identify 548 potentially-amplifiable simple sequence repeat loci and 689 expressed transposable elements.</p> <p>Conclusions</p> <p>This study is the first comprehensive transcriptome analysis for a fern and represents an important scientific resource for comparative evolutionary and functional genomics studies in land plants. We demonstrate the utility of high-throughput sequencing of a normalized cDNA library for <it>de novo </it>transcriptome characterization and gene discovery in a non-model plant.</p

Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective

Data-driven decision making is becoming an integral part of manufacturing companies. Data is collected and commonly used to improve efficiency and produce high quality items for the customers. IoT-based and other forms of object tracking are an emerging tool for collecting movement data of objects/entities (e.g. human workers, moving vehicles, trolleys etc.) over space and time. Movement data can provide valuable insights like process bottlenecks, resource utilization, effective working time etc. that can be used for decision making and improving efficiency. Turning movement data into valuable information for industrial management and decision making requires analysis methods. We refer to this process as movement analytics. The purpose of this document is to review the current state of work for movement analytics both in manufacturing and more broadly. We survey relevant work from both a theoretical perspective and an application perspective. From the theoretical perspective, we put an emphasis on useful methods from two research areas: machine learning, and logic-based knowledge representation. We also review their combinations in view of movement analytics, and we discuss promising areas for future development and application. Furthermore, we touch on constraint optimization. From an application perspective, we review applications of these methods to movement analytics in a general sense and across various industries. We also describe currently available commercial off-the-shelf products for tracking in manufacturing, and we overview main concepts of digital twins and their applications

National Center for Genome Analysis Program Year 3 Report – September 15, 2013 – September 14, 2014

On September 15, 2011, Indiana University (IU) received three years of support to establish the National Center for Genome Analysis Support (NCGAS). This technical report describes the activities of the third 12 months of NCGASThe facilities supported by the Research Technologies division at Indiana University are supported by a number of grants. The authors would like to acknowledge that although the National Center for Genome Analysis Support is funded by NSF 1062432, our work would not be possible without the generous support of the following awards received by our parent organization, the Pervasive Technology Institute at Indiana University. • The Indiana University Pervasive Technology Institute was supported in part by two grants from the Lilly Endowment, Inc. • NCGAS has also been supported directly by the Indiana METACyt Initiative. The Indiana METACyt Initiative of Indiana University is supported in part by the Lilly Endowment, Inc. • This material is based in part upon work supported by the National Science Foundation under Grant No. CNS-0521433. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF)

5.Uluslararası Öğrenciler Fen Bilimleri Kongresi Tam Metin Kitabı

Çevrimiçi (IX, 431 Sayfa; 26 cm.)