The rapid changes in customer demand force manufacturers to develop new technologies for flexibility enhancement in the manufacturing system. Different kinds of literature are available to explain the issues in the Flexible manufacturing system (FMS) and different traditional techniques employed for solving such issues. However, several new techniques have emerged in the past 25 years and no literature reviews exist to differentiate such modern approaches from traditional ones. The core purpose of this review is to study and investigate different levels of techniques involved in the effective implementation of FMS. This paper serves with some reasonable investigation of flexible issues faced in manufacturing industries such as scheduling, machine loading, material handling, and decision-making stage. For each manufacturing issue, the emerged manufacturing techniques are described in this review. This will also help future researchers interested in doing their research work in the area of FMS. It provides information to develop the best model for solving issues of the observed FMS problem. This paper contains the details of issues related to flexibility in manufacturing sectors with its resolving techniques that are reviewed and symbolized between the years 2000 and 2021.

Electrochemical Discharge Machining (ECDM) has combined characteristics of ECM and EDM which is effectively been used for machining electrically nonconductive, hard, and brittle materials like glass, quartz, and ceramics. However, the industrial application of this process is limited due to difficulty in machining micro holes with higher machined depth. To improve the machining performance of the ECDM process, loose abrasive particles have been mixed in an electrolyte while machining blind holes on soda–lime glass. This study is mainly focused on investigating the effect of process parameters (voltage and electrolyte concentration) on the responses (volume of material removed, machined depth and overcut) using CCRD. The significance of process parameters on the responses has been evaluated using ANOVA. A second-order regression equation has been developed for predicting the relation between input process parameters and quality characteristics (i.e. volume of material removed, diameter overcut, and machined depth). It is observed that the addition of Al2O3 abrasives has improved the volume of material removed and machined depth. On the other hand, the addition of SiC abrasives into the electrolyte has reduced the diametric overcut due to their specific characteristic.

With the rapid development of the social economy, the requirements for the production efficiency of job shop have also increased, but the production efficiency of the traditional flow shop is no longer suitable for the efficient speed of economic development. Therefore, it is an urgent task to study the problem of optimal scheduling of flow shop. In this study, the problem of optimal scheduling of the flow shop was taken as the main research subject, the machining sequence and maximum completion time were taken as the key points, a method of optimal scheduling by genetic algorithm (GA) was proposed, and a mathematical model for optimal scheduling of the flow shop based on GA was established. The optimal processing sequence of the six jobs in the production was obtained: 2–1–6–5–4–3; the average completion time was 381.6[Formula: see text]min, and the optimal solution frequency was 0.8. Moreover, the total processing time of the GA-based flow shop was shorter than that of the traditional flow shop. This work provides a new route for the optimal scheduling of flow shop.

In order to accurately define the nanomechanical performance parameters of single crystal gallium oxide, the microscopic deformation mechanism during processing is analyzed. On the G200 nanoindenter, the Berkovich indenter made of diamond was used to perform nanoindentation experiments on single crystal gallium oxide (100) and (010) crystal planes by using a quasi-static method to set the load. According to the power law relationship and Nix-Gao model proposed by Manika, the relationship between the hardness of the two crystal faces of single crystal gallium oxide and the depth of indentation is fitted, and the single crystal gallium oxide (100) and (010) crystal faces without considering the size influence factor. The hardness is 8.238[Formula: see text]GPa and 9.824[Formula: see text]GPa, the micro feature length is 101.196[Formula: see text]nm and 88.033[Formula: see text]nm, and the size influence factor is 0.1725 and 0.1706, respectively. The size influencing factors of the two crystal planes are between common metal materials and semiconductor materials. Compared with the (010) crystal plane, the (100) plane exhibits a larger elastic modulus and lower hardness. (100) The indentation size effect of the crystal plane is more obvious.

Nowadays, the management of soil resources for global food security is one of the strategic purposes of the countries. In this regard, creating soil nutrition’s supply chain network for the fertility of agricultural fields is one of the most critical priorities of the government. In the above strategic network, we are faced with uncertain parameters that show a complex behavior under time, geography, and market changes. This parametric uncertainty is aggravated by the occurrence of disruptions such as sanctions and natural disasters, with devastating effects on strategic, tactical, and operational decisions. In this paper, by adopting a set of reactive and preventive strategies, the resilient supply chain network of dependent petrochemical industries is presented, consistent with the structure of its production cycle in Iran. To cope with the uncertainty, a robust programming approach was extended into flexible-possibilistic programming. The final model controls the uncertainty and risk-aversion of output decisions and effectively confronts the adverse effects of disruptions. Finally, using a real industrial study, the effectiveness and applicability of the final model are explained. Furthermore, by providing efficient solutions, mean cost and minimum standard deviations were achieved.

In present investigations, Co–Cr alloy powder is deposited on SS 316L substrate material by plasma transferred arc welding (PTAW) technique. Analysis is carried out by evaluating the different processing conditions as per the design of experiments by response surface methodology. Efforts are made to investigate PTAW overlay process on two compound parametric approaches governing deposition characteristics. First approach focuses on the actual mass of powder deposited by melting over a substrate surface which governs deposition efficiency and second approach reflects the heat energy supplied to the arc region causing melting of both supplied powder and substrate material resulting distortion. The deposition efficiency and distortion of substrate material are measured for each experimental condition and the effect of transferred arc current, travel speed, powder feed rate, oscillation speed and stand-off distance are investigated. For deposition efficiency, the powder feed rate is the most important process parameter and powder feed rate between 8[Formula: see text]g/min and 12[Formula: see text]g/min contributes excellent deposition efficiency. For deformation, the transferred arc current is the most sensitive process parameter and low current conditions, 100–120[Formula: see text]A showed less distortion in the specimen. In order to achieve good deposition efficiency and less distortion, it is recommended to carry out PTAW deposition with arc current 120[Formula: see text]A, travel speed 120[Formula: see text]mm/min, powder feed rate 11[Formula: see text]g/min and stand-off distance 8[Formula: see text]mm.

Many scholars mentioned various dimensions and complex relations for manufacturing flexibility that implementing all of them is not possible for a manufacturing firm. On the other hand, today’s dynamic environment convinces flexible organizations to create capabilities in order to take over competitors. Hence, the aim of this study is to determine dominant groups of flexibility for manufacturing firms and to prioritize them under the influence of dynamic organizational capabilities. In this research, firstly components of dynamic organizational capabilities and flexibility of manufacturing are identified by content analysis method. Then, based on that, taxonomy for Iran’s manufacturing firms was determined using support vector machine algorithm. In the next step, based on experts’ view using FDEMATEL method, conceptual model for relationship of manufacturing flexibility dimension as well as dynamic capabilities are provided. Conceptual model in three flexibility clusters was tested by structural equation modeling, and dominant groups were prioritized based on dynamic organizational capabilities. Results show that the best number of clusters is three. Results also show that dynamic organizational capabilities not only affect flexibility dimensions of manufacturing but also this influence is different in manufacturing firms with various industry fields.

The paper discusses a unique technique developed initially at Nation Institute of Technology, Surat that is remodeled in real-world applications. The concept consists primarily of a user-friendly software facilitating direct communication with any intelligent or learning system/robot operating under known parameters of motor specifications. Any software base permitting high level PC interface without ASCII interrupt can be used for easy programming. This allows for a learning operation mode where a prevention of time lag is enabled by stored machine data, captured through movements such movements can be physically made or taught via programs to the device and such learning aspects make the machine more efficient where the robot can either perform individual actions as needed or learn new methods for the same results and can perform a series of actions continuously. Using the stored data, the machine is also capable of autonomous movements based on the path of least resistance as calculated by the time it takes to perform an act. Interfacing Technique Tool Machining Robot (ITTMR) was developed as robotic tool holder that can determine the shape and size of different OCTG pipes utilized in the downhole industry and enable it to machine appropriate threads on the pipe with no manual intervention. The process thereby completely negates any possibility of human error which can otherwise cause heavy loss on finished equipment that are rendered unusable because of threading errors on almost nearly finished complex milled parts or assemblies that are pending threads as the final operation. The purpose of the software codes is to provide a user-friendly GUI that can communicate with any machine by pulling in appropriate ACNC programs and performing the required tasks associated with the operating system and specifications of the motors/mobilization equipment’s used. For the purpose of this paper, the software code is not provided. Any firmware base that permits the usage of an ASCII interrupt can be used and for the purpose of this operation, an RS323 equivalent board will also suffice for basic operations, however a complex ITTMR system has been utilized. This paper solely addresses the technique of how the threading operation is performed and does not address the process of how the pipe is bought to the machine or other associated aspects of the software to retain any possible patent applications on the same.

The purpose of this paper is to provide a practical approach of prioritizing the most critical success factors influencing the supply chain performance in SMEs by using an interpretive structural modeling (ISM) approach. The MICMAC analysis has been also considered for identifying the factors having a high influential power. Our findings show that, on the one hand, the production system, flexibility, communication and planning tools, process strategy, environmental uncertainty and innovation are the major factors influencing the supply chain performance. On the other hand, relationships with customers and suppliers, marketing and quality are seen as unfavorable outcomes to the supply chain managers and practitioners. These findings may help the policy makers, managers, and practitioners in formulating the strategies and policies for implementation of effectiveness supply chain.

This paper demonstrates an exclusive design methodology in Cellular Manufacturing (CM) considering machine usage percentage as ratio data. This research correctly emphasized the fundamental of ratio data and proposed a novel and precise mathematical formulation of the design problem. This multi-objective model carefully optimizes the total exceptional utilization (TEU), number of voids and total cell utilization (TCU). Due to the novelty in the model, a new data generation technique is proposed. The test datasets are obtained and tested using IBM CPLEX tool successfully. The contribution of this research is twofold. First, the ratio data concept is correctly emphasized and a precise mathematical model is developed. Second, since the model is new and datasets are not readily available, therefore a dedicated data generation model is proposed.