Product family formation and selection for reconfigurability using analytical network process

The paper develops a conceptual framework for product family formation towards reconfigurability through proposing a product-process reconfiguration link. Different decisive factors affecting product family formation and selection such as manufacturing requirements, market requirements, manufacturing cost and process reconfiguration are investigated. An analytical network process (ANP) model is proposed to incorporate all the outlined decisive factors and major criteria and elements influencing the product family formation and selection. As a consequence of the interactive nature of the product family selection problem, most of the children's’ elements within the same cluster and/ or different clusters are associated with each other. As a result, all the clusters are connected to each other (outer dependencies) as well as their connections to themselves (inner dependencies). The proposed ANP model is examined through a case study in a manufacturing company for validation. Synthesis judgments and sensitivity analysis are carried out for selecting the most appropriate product family along with analysing the influence of the selected critical elements.     

Multi-objective multi-unit process plan generation in a reconfigurable manufacturing environment: a comparative study of three hybrid metaheuristics

Low costs, high reactivity and high quality products are necessary criteria for industries to achieve competitiveness in nowadays market. In this context, reconfigurable manufacturing systems (RMSs) have emerged to fulfil these requirements. RMS is one of the latest manufacturing paradigms, where machines components, software or material handling units can be added, removed, modified or interchanged as needed and when imposed by the necessity to react and respond rapidly and cost-effectively to changing. This research work addresses the multi-objective single-product multi-unit process plan generation problem in a reconfigurable manufacturing environment where three hybrid heuristics are proposed and compared namely: repetitive single-unit process plan heuristic (RSUPP), iterated local search on single-unit process plans heuristic (LSSUPP) and archive-based iterated local search heuristic (ABILS). Single-unit process plans are generated using the adapted non-dominated sorting genetic algorithm (NSGA-II). Moreover, in addition to the minimisation of the classical total production cost and the total completion time, the minimisation of the maximum machines exploitation time is considered as a novel optimisation criterion, in order to have high quality products. To illustrate the applicability of the three approaches, examples are presented and the obtained numerical results are analysed.     

A methodology for design and reconfiguration of reconfigurable bending press machines (RBPMs)

Customer requirements have become very dynamic and unprecedented. A manufacturing paradigm called reconfigurable manufacturing system was initiated to adjust the physical machine entities. The main enabler of a machine structure’s reconfigurability is a modular design approach. The paper explains a function-driven object-oriented methodology for the design and reconfiguration of RBPMs. The complete method aims to optimise initial design of RBPMs, followed by subsequent design of RPBM modules which are stored in a module library so as to enable full-automatic reconfiguration of the RBPMs. The methodology is implemented on a pilot project to design a 145 ton bending capacity RBPM, with a maximum reconfigured length of 5?m and total height of 3?m. In order to deduce the design for the reconfigurable bending press machine, the reconfigurability needs were identified first, followed by the construction of a function tree for the machine. The function tree identifies the primary function for the RBPM, which is to bend sheet metal. The primary function is further decomposed to lower level functions until terminal functions are arrived at. The terminal functions are then used to identify the modules for the machine. The modules implement specific brunches of the machine functions.     

Multi-objective sustainable process plan generation in a reconfigurable manufacturing environment: exact and adapted evolutionary approaches

Achieving competitiveness in nowadays manufacturing market goes through being cost and time-efficient as well as environmentally harmless. Reconfigurable manufacturing system (RMS) is a paradigm that is able to meet these challenges due to its scalability and integrability. In this paper, we aim to solve the multi-objective sustainable process plan generation problem in a reconfigurable environment. In addition to the total production cost and the completion time, we use the amount of greenhouse gases (GHG) emitted during the manufacturing process as a sustainability criterion. We propose an iterative multi-objective integer linear programming (I-MOILP) approach and its comparison with adapted versions of the two well-known evolutionary algorithms, respectively, the Archived Multi-Objective Simulated Annealing (AMOSA) and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Moreover, we study the influence of the probabilities of genetic operators on the convergence of the adapted NSGA-II. To illustrate the applicability of the three approaches, an example is presented and obtained numerical results analysed.     

Configuration design in scalable reconfigurable manufacturing systems (RMS); a case of single-product flow line (SPFL)

The dynamic nature of today’s manufacturing industry, which is caused by the intense global competition and constant technological advancements, requires systems that are highly adaptive and responsive to demand fluctuations. Reconfigurable manufacturing systems (RMS) enable such responsiveness through their main characteristics. This paper addresses the problem of RMS configuration design, where the demand of a single product varies throughout its production life cycle, and the system configuration must change accordingly to satisfy the required demand with minimum cost. A two-phased method is developed to handle the primary system configuration design and the necessary system reconfigurations according to demand rate changes. This method takes advantage of Reconfigurable Machine Tools in RMS. In fact, by adding/removing modules to/from a specific modular reconfigurable machine, its production capability could be increased, with lower cost. A novel mixed integer linear programming formulation is presented in the second phase of the method to optimise the process of selecting the best possible transformation for the existing machine configurations. Two different cases are designed and solved by implementing the established method. The results of these cases in terms of capital cost, capacity expansion cost, unused capacity and number of transformations, are compared with two hypothetical scenarios. Analyses of the obtained results indicate the efficiency of the proposed approach and offer a promising outlook for further research.     

Delayed reconfigurable manufacturing system

Reconfigurable manufacturing systems (RMS) is a new manufacturing paradigm aiming at providing exactly functionality and capacity needed and exactly when needed. Reconfiguration is the main method to achieve this goal. But, the reconfiguration is an interruption to production activities causing production loss and system ramp-up problem and the ‘exact functionality’ may increase the reconfiguration efforts and aggravate the production loss and the ramp-up time. Therefore, a special RMS – delayed reconfigurable manufacturing system (D-RMS) is proposed to promote the practicality of RMS. Starting from the RMS built around part family with the characteristic of delayed differentiation, whose reconfiguration activities mainly occur in the latter stages of manufacturing system and the former stages have the potential to maintain partial production activities to reduce production loss during reconfiguration. Inspired from this, the basic structure of RMS is divided into two subsystems, subsystem 1 is capable of maintain partial production with a certain more functionality than needed, subsystem 2 reconfigure to provide exactly functionality and capacity of a specific part exactly when needed. And then, the benefits of D-RMS are analysed from inventory and ramp-up time aspects. Finally, a case study is presented to show the implementation process of D-RMS and validates the practicability of D-RMS.     

快速重组制造系统的构建原理及其应用

快速重组制造系统是一种适应21世纪全球化市场竞争的新型制造系统。提出了基于组态式柔性制造单元组成的陈列式布局的快速重组制造系统的创新结构体系,建立了以生产效益为该系统方案设计和运行决策目标的随机模型,应用排队网络模型和静态马尔科夫工件运送方式得出系统重组时缓冲区容量的优化配置和最优工件运送策略的算法,研制了作为构建快速重组制造系统核心的新颖的组态式柔性制造单元的原型,并给出生产工程中应用所创建的阵列式可重组制造系统的成功案例。     

Identifying inventory problems in the aerospace industry using the theory of constraints

In the aerospace industry, where each component is time-critical, many operation management tools are applied to improve material management efficiency. By using the theory of constraints (TOCs), this study diagnoses the undesirable effects (UDEs) of material management systems and identifies root problems or conflicting material management actions. In the second step, via UDEs, this study constructs a current reality tree (CRT) to identify a company's material management objectives and requirements, and the actions it takes to meet these objectives. In addition, the UDEs and CRT are applied to redesign the future reality tree (FRT) to develop strategies and eliminate the problems in the case company. By eliminating the conflicting inventory management activities of different departments, inventory management performance for the entire system is improved.     

制约理论之思维流程在某制造企业的应用

按照思维流程的三条逻辑脉络:改变什么,改成什么样,怎样去改.以某制造企业为例说明了TP的五大逻辑关系图:当前现实树、冲突化解图、未来现实树、必备树和转移树的运用过程,以帮助企业发现核心问题,找到解决问题的方案并采取行动最终解决问题.     

Differential quadrature method for nonlocal nonlinear vibration analysis of a boron nitride nanotube using sinusoidal shear deformation theory

This article presents a nonlocal sinusoidal shear deformation beam theory (SDBT) for the nonlinear vibration of single-walled boron nitride nanotubes (SWBNNTs). The surrounding elastic medium is simulated based on nonlinear Pasternak foundation. Based on the nonlocal differential constitutive relations of Eringen, the equations of motion of the SWBNNTs are derived using Hamilton's principle. Differential quadrature method (DQM) for the nonlinear frequency is presented, and the obtained results are compared with those predicted by the nonlocal Timoshenko beam theory (TBT). The effects of nonlocal parameter, vibrational modes, length, and elastic medium on the nonlinear frequency of SWBNNTs are considered.     

Coverage‐based vulnerability discovery modeling to optimize disclosure time using multiattribute approach

Software vulnerabilities trend over time has been proposed by various researchers and academicians in recent years. But none of them have considered operational coverage function in vulnerability discovery modeling. In this research paper, we have proposed a generalized statistical model that determines the relationship between operational coverage function and the number of expected vulnerabilities. During the operational phase, possible vulnerable sites are covered and vulnerabilities present at a particular site are discovered with some probability. We have assumed that the proposed model follows the nonhomogeneous Poisson process properties; thus, different distributions are used to formulate the model. The numerical illustration shows that the proposed model performs better and has the good fitness to the Google Chrome data. The second focus of this research paper is to evaluate the total cost incurred by the developer after software release and to identify the optimal vulnerability disclosure time through multiobjective utility function. The proposed vulnerability discovery helps in optimization. The optimal time problem depends on the combined effect of cost, risk, and effort.     

中国工业工程学科发展现状与趋势

回顾了中国工业工程（ＣＩＥ）学科产生和发展的历程，提出了ＣＩＥ的理论概念，并对其技术体系和发展趋势进行了探讨。     

Sequencing of parts on single-stage multifunctional machining systems using a chaos-embedded simulated annealing algorithm

This paper deals with the objective of determining an optimal part sequence on a single-stage multifunctional machining system (SSMS) with a view to achieve the broad objectives of cost minimization and time minimization. SSMS has become a preferred alternative for manufacturers to use the resource efficiently, owing to the flexibility and process variety offered by it. This paper formulates a mathematical model that considers the minimization of both set-up cost and time simultaneously. The option of hiring an additional fixture has also been considered that enables the reduction in tool magazine replenishment and re-fixturing operations, which in turn offers economic advantage by way of reducing set-up cost. This study has proposed a new heuristic by modifying the simulated annealing concept to solve the underlying problem. The conventional simulated annealing search scheme is replaced by a chaotic search that takes into account the ergodic and stochastic properties of chaotic systems. In order to restrict the premature convergence and to diversify the search space, a modified perturbation scheme has been employed. The performance of the proposed algorithm was tested on a simulated case study adopted from the literature and the results obtained reveal the effectiveness and scalability of the proposed algorithm. The results establish that the proposed approach is effective and reactive to severe disturbances and must take place in the manufacturing environment.     

Mechanical system reliability analysis using a combination of graph theory and Boolean function

A new method based on graph theory and Boolean function for assessing reliability of mechanical systems is proposed. The procedure for this approach consists of two parts. By using the graph theory, the formula for the reliability of a mechanical system that considers the interrelations of subsystems or components is generated. Use of the Boolean function to examine the failure interactions of two particular elements of the system, followed with demonstrations of how to incorporate such failure dependencies into the analysis of larger systems, a constructive algorithm for quantifying the genuine interconnections between the subsystems or components is provided. The combination of graph theory and Boolean function provides an effective way to evaluate the reliability of a large, complex mechanical system. A numerical example demonstrates that this method an effective approaches in system reliability analysis.     

Material removal at atomic and close-to-atomic scale by high-energy photon:a case study using atomistic-continuum method

Extreme ultraviolet (EUV) light plays an important role in various fields such as material characterization and semiconductor manufacturing. It is also a potential approach in material fabrication at atomic and close-to-atomic scales. However, the material removal mechanism has not yet been fully understood. This paper studies the interaction of a femtosecond EUV pulse with monocrystalline silicon using molecular dynamics (MD) coupled with a two-temperature model (TTM). The photoionization mechanism, an important process occurring at a short wavelength, is introduced to the simulation and the results are compared with those of the traditional model. Dynamical processes including photoionization, atom desorption, and laser-induced shockwave are discussed under various fluencies, and the possibility of single atomic layer removal is explored. Results show that photoionization and the corresponding bond breakage are the main reasons of atom desorption. The method developed can be further employed to investigate the interaction between high-energy photons and the material at moderate fluence.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00374-x     

Developing a practical framework for assessing ERP post-implementation success using fuzzy analytic network process

Implementing an enterprise resource planning system is a sophisticated, lengthy, and costly process which tends to face serious failure. Thus, it is essential to perform a success assessment at the post-implementation stage of an ERP project to evaluate how much the system has succeeded in achieving its predetermined objectives. This paper proposes a practical framework for assessing a firm's ERP post-implementation success utilising current models through a fuzzy analytic network process. The construct of ERP success is broken down into three main parts, including managerial success, organisational success, and individual success. Using this framework, the firm's ERP system success can be determined and the required improvement projects can be proposed to promote the success level. The proposed framework has been applied to a real international company, in the field of manufacturing and supplying turbines, to measure the firm's ERP post-implementation success. Finally, the advantages of the model are illustrated.     

Developing a New qPCR‐Based System for Screening Mutation

An accurate genotyping analysis is one of the critical prerequisites for lung cancer targeted therapy. Here, a quantitative polymerase chain reaction (qPCR)‐based mutation detection system, mutation‐selected amplification‐specific system PCR (MASS‐PCR), is developed. The specific primers and probes used in MASS‐PCR exactly match with the mutant sequence that only allows mutant gene to emit the fluorescence peak. To determine the sensitivity of MASS‐PCR, 717 lung cancer specimens, 61 formalin‐fixed paraffin‐embedded (FFPE) tissues, and 656 fresh reaction tissues are collected and undergo mutation detection of lung cancer driver genes (EGFR, KRAS, BRAF, HER2, MET, ALK, and ROS1). These samples are divided into two groups. Mutations in Group I, which has 631 fresh reaction tissues, are analyzed by MASS‐PCR and the amplification refractory mutation system PCR (ARMS‐PCR). While group II samples, 25 fresh reaction tissues and 61 FFPE tissues, are screened through MASS‐PCR and next‐generation sequencing (NGS). All results are verified by direct sequencing. MASS‐PCR shows high consistency with ARMS‐PCR (kappa value > 0.733) and NGS (kappa value = 0.79) (P < 0.001). For the samples with inconsistent MASS‐PCR and ARMS‐PCR results, DS results more likely support the MASS‐PCR results. These data suggest that MASS‐PCR is a convenient, accurate, and economical method for the detection of lung cancer driver gene mutations in clinical practice.     

Effect of stepover and torch tilting angle on a repair process using WAAM

To sustain the transition to a greener economy and greener manufacturing, it is necessary to develop new approaches and technologies to repair metal components; this will result in a drastic reduction in energy and material usage. In this study, wire arc additive manufacturing (WAAM) was used to deposit a layer of new material on an existing surface, with the objective of finding the optimal configuration that maximized the layer quality and material efficiency. The parameters considered are the stepover among the deposited beads and the inclination of the torch with respect to the repaired surfaces. The inclination angle is crucial when repairing complex surfaces, like those of a mold, owing to accessibility issues, the torch cannot be maintained orthogonal to the surfaces along the entire toolpath. Different configurations were tested in order to assess the quality of the materials in terms of the presence of material voids, depth of penetration, and the heat affected zone (HAZ) and to understand the effects of these variables on the material efficiency and thickness of the repairing layer. It should be noted that by adopting deposition parameters set to have a low heat input, the use of a tilting angle has beneficial effects on the quality of the deposited layer and the process efficiency. Metallurgical and geometrical measurements were carried out to assess the effect of these two variables depositing a layer of plain carbon steel.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-022-00393-2     

Characteristics of a long-period fiber grating with reduced cladding for refractive index sensing

The sensitivity to surrounding refractive index (SRI) of a long-period fiber grating (LPFG) can be effectively improved by decreasing the cladding radius. When the cladding is reduced, a three-layer model is necessary to evaluate the effective refractive index (ERI) of the core mode. A variation of SRI can induce a greater resonant wavelength shift when the core mode is coupled to a higher-order cladding mode. However, as the cladding is reduced further, the highest-order cladding mode would be cut off, i.e. the number of cladding modes that a given fiber structure can support would be less; thus, the higher-order cladding modes that can be used for higher sensitivity are limited. Hence, the implementation of high sensitivity for SRI sensing with cladding-reduced LPFGs is dependent on the proper combination of cladding radius and cladding mode order. Based on the vector coupled-mode theory, the transmission spectrum and sensitivity are numerically analyzed with respect to the cladding radius, which shows that the SRI sensitivity of the HE₁₂ mode with cladding radius a ₂?=?20?µm is 32 times as high as that with a ₂?=?62.5?µm and the SRI resolution is available to the order of 10^?7.