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The purpose of this paper is to present a shape optimization technique for powder forming processes based on the genetic algorithm approach. The genetic algorithm is employed to optimize the geometry of component based on a fixed‐length vector of design variables representing the changes in nodal coordinates. The technique is used to obtain the desired optimal compacted component by changing the boundaries of component and verifying the prescribed constraints.

The numerical modeling of powder compaction simulation is applied based on a large deformation formulation, powder plasticity behavior, and frictional contact algorithm. A Lagrangian finite element formulation is employed for large powder deformations. A cap plasticity model is used in numerical simulation of nonlinear powder behavior. The influence of powder‐tool friction is simulated by the use of penalty approach in which a plasticity theory of friction is incorporated to model sliding resistance at the powder‐tool interface.

Finally, numerical examples are analyzed to demonstrate the feasibility of the proposed optimization algorithm for designing powder components in the forming process of powder compaction.

A shape optimization technique is presented for powder forming processes based on the genetic algorithm approach.

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.

The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.

The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.

In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.

The study presents the case of an automotive component, which illustrates practical relevance.

In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Garment manufacturing is a traditional industry with global competition. The most critical part is streamline, as it generally involves a great number of operations. The purpose of this paper is to, based on the model of group technology (GT), sum up the methods of assembly line optimization to optimize the streamline, so that the machines of the workstation can perform the assigned tasks with a balanced loading.

In this paper, the methods of obtaining and optimizing data includes literature, research and optimization methods of basing on GT model. The main direction of literature has two aspects: Lean production theory and streamline assignment. Research mainly concludes three aspects: research place, research object and the research content. The method of time determination is averaging the testing values of repeated measurements. Optimization methods of basing on GT model mainly include combination of the same type of technologic processes in sequence, combination of independent branch process, the combination of mainstream and branch processes and offside combination of the same type of processes.

After optimization, in the utilization rate of equipment: hanging system ratio was increased from 22.95 to 62.12 percent, which greatly improved the utilization rate of enterprise equipment. In equipment layout: hanging equipment layout was turned linear type into “U” type, which realized the synchronization of production. GT model will be well applied in the garment production streamline. Compared with other enterprises, A company has large garment hanging system, which reflects the advanced, comprehensive, representative. Therefore, the paper applied optimization methods to trousers, production efficiency has been improved greatly, the utilization rate of equipment is promoted and reworking phenomenon is reduced greatly.

Through the optimization of the production process and equipment layout, the A company’s compiling efficiency has been greatly improved, but how can the system become computerized, accurately and intelligence, which has been an important direction of research now.

By optimizing, it is fully proved that applying GT to the streamline optimization is feasible. GT is an important branch of Lean production, summing up the optimization methods basing on the GT model to optimize the streamline not only enriches the relevant theory research, but also provides a theoretical basis for the practical production. GT model not only can be used in the shirt production process, as for other production processes, for example, trousers, skirts can also be widely applied, which realizes the theory application in the practical production.

The originality of this paper is that through the analysis of the model of GT, the paper sums up the methods of assembly line optimization to optimize the streamline. Although the model of GT is used widely in electronics, automobile and industry, it is relatively weak in the optimization of garment production line, there are not many literatures on practical application of group technology in the clothing. Besides, the paper is applied to practical production, which not only can improve production efficiency, but also make the theoretical research have basis and combine the theory and practical production.

The purpose of this paper is to propose an integrated approach to process integration, automation, and optimization through enhanced business process models.

The approach is based on a framework of process integration for functional applications, automation for business workflows, and additional functionalities for process optimization. The proposed approach is illustrated using enhanced process models over business integration, automation, and optimization with data elements, structures, and organizational elements. The standard sales order process cycle, quotation approval process, and production order cycle are chosen for illustrating process integration, automation, and optimization, respectively.

The proposed approach combines applications and workflows using integrated process/data models and forms a foundation for business process optimization. It is shown that the integrated approach can improve existing business processes in enterprise resource planning (ERP), beyond business process re‐engineering (BPR) principles, once enhanced business process models are implemented. This approach eliminates need for a hierarchical representation of business processes and highlights the flexibility and visibility of business process implementation in ERP system environment.

Although process integration, automation, and optimization are illustrated using selected business process examples, it requires generalization of these enhancements over entire business blueprint of ERP system. Thus, one key limitation of this research is that it is not generalized for the entire business blueprint of ERP. This also requires changes to data structures beyond current relational data in many ERP systems.

This research provides an integrated approach to business process modeling beyond traditional functional and workflow applications by eliminating hierarchical nature of process and data elements.

Methods to optimize lattice structure design, such as ground structure optimization, have been shown to be useful when generating efficient design concepts with complex truss-like cellular structures. Unfortunately, designs suggested by lattice structure optimization methods are often infeasible because the obtained cross-sectional parameter values cannot be fabricated by additive manufacturing (AM) processes, and it is often very difficult to transform a design proposal into one that can be additively designed. This paper aims to propose an improved, two-phase lattice structure optimization framework that considers manufacturing constraints for the AM process.

The proposed framework uses a conventional ground structure optimization method in the first phase. In the second phase, the results from the ground structure optimization are modified according to the pre-determined manufacturing constraints using a second optimization procedure. To decrease the computational cost of the optimization process, an efficient gradient-based optimization algorithm, namely, the method of feasible directions (MFDs), is integrated into this framework. The developed framework is applied to three different design examples. The efficacy of the framework is compared to that of existing lattice structure optimization methods.

The proposed optimization framework provided designs more efficiently and with better performance than the existing optimization methods.

The proposed framework can be used effectively for optimizing complex lattice-based structures.

An improved optimization framework that efficiently considers the AM constraints was reported for the design of lattice-based structures.

The purpose of this article is to analyze the optimization process in depth, elaborating on the components of the entire process and the techniques used. Researchers have been drawn to the expanding trend of optimization since the turn of the century. The rate of research can be used to measure the progress and increase of this optimization procedure. This study is phenomenal to understand the optimization process and different algorithms in addition to their application by keeping in mind the current computational power that has increased the implementation for several engineering applications.

Two-dimensional analysis has been carried out for the optimization process and its approaches to addressing optimization problems, i.e. computational power has increased the implementation. The first section focuses on a thorough examination of the optimization process, its objectives and the development of processes. Second, techniques of the optimization process have been evaluated, as well as some new ones that have emerged to overcome the above-mentioned problems.

This paper provided detailed knowledge of optimization, several approaches and their applications in civil engineering, i.e. structural, geotechnical, hydraulic, transportation and many more. This research provided tremendous emerging techniques, where the lack of exploratory studies is to be approached soon.

Optimization processes have been studied for a very long time, in engineering, but the current computational power has increased the implementation for several engineering applications. Besides that, different techniques and their prediction modes often require high computational strength, such parameters can be mitigated with the use of different techniques to reduce computational cost and increase accuracy.

This paper aims to summarize design rules based on the process characteristics of selective laser melting (SLM) and structural optimization and apply the design rules in the lightweight design of an aluminum alloy antenna bracket. The design goal is to reduce 30 per cent of the weight while maintaining the stress levels in the original part.

To reduce weight as much as possible, the titanium alloy with higher specific strength was selected during the process of optimization. The material distribution of the bracket was improved by the topology optimization design. The redesign for SLM was used to obtain an optimization model, which was more suitable for SLM. The component performance was improved by shape optimization. The modal analysis data of the structural optimization model were compared with those of the stochastic lightweight model to verify the structural optimization model. The scanning data were compared with those of the original model to verify whether the model was suitable for SLM.

Structural optimization design for antenna bracket realized the mass decrease of 30.43 per cent and the fundamental frequency increase of 50.18 per cent. The modal analysis data of the stochastic lightweight model and the structural optimization model indicated that the optimization performance of structural optimization method was better than that of the stochastic lightweight method. The comparison results between the scanning data of the forming part and the original data confirmed that the structural optimization design for SLM lightweight component could achieve the desired forming accuracy.

This paper summarizes geometric constraints in SLM and derives design rules of structural optimization based on the process characteristics of SLM. SLM design rules make structural optimization design more reasonable. The combination of structural optimization design and SLM can improve the performance of lightweight antenna bracket significantly.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

The purpose of this paper is to present an application of a multidisciplinary multi-level design optimization methodology for the optimal design of a complex device from the field of electrical engineering throughout discipline-based decomposition. The considered benchmark is a single-phase low voltage safety isolation transformer.

The multidisciplinary optimization of a safety isolation transformer is addressed within this paper. The bi-level collaborative optimization (CO) strategy is employed to coordinate the optimization of the different disciplinary analytical models of the transformer (no-load and full-load electromagnetic models and thermal model). The results represent the joint decision of the three distinct disciplinary optimizers involved in the design process, under the coordination of the CO's master optimizer. In order to validate the proposed approach, the results are compared to those obtained using a classical single-level optimization method – sequential quadratic programming – carried out using a multidisciplinary feasible formulation for handling the evaluation of the coupling model of the transformer.

Results show a good convergence of the CO process with the analytical modeling of the transformer, with a reduced number of coordination iterations. However, a relatively important number of disciplinary models evaluations were required by the local optimizers.

The CO multi-level methodology represents a new approach in the field of electrical engineering. The advantage of this approach consists in that it integrates decisions from different teams of specialists within the optimal design process of complex systems and all exchanges are managed within a unique coordination process.