Search results

During design of reconfigurable manufacturing systems, manufacturing companies need to select and implement the right enablers of reconfigurability in accordance with the specific requirements being present in the manufacturing setting. Therefore, the purpose of this paper is to investigate enablers of reconfigurability in terms of their importance in industry, current level of implementation in industry, and significant differences in their implementation and criticality across different manufacturing settings.

A questionnaire survey is conducted, in order to provide generalizable empirical evidence across various industries and manufacturing types.

The findings indicate that the level of implementation of the reconfigurability enablers is rudimentary, while their criticality is perceived higher than the current level of implementation. Moreover, significant differences regarding implementation and criticality of mobility, scalability, and convertibility were found for companies with varying degrees of manual work, make-to-stock production, and varying production volume, industry type and organization size.

Main limitations of the research cover the relatively small sample size and non-random sampling method applied, primarily limited to one country, which could be increased to further extent the findings reported in this paper.

The findings indicate that the importance and implementation of reconfigurability enablers is contingent on the manufacturing setting. Thus, the research presented in this paper provides valuable knowledge in regard to aiding a paradigm shift in industry and help companies design manufacturing systems with the right reconfigurability enablers.

This paper expands research on manufacturing system design for changeability and reconfigurability, by explicitly considering these as capabilities that can be enabled in various ways for various purposes in different manufacturing contexts.

Production of a high variety of products introduces complexities in the quality processes involved in a manufacturing system. Previous methods of quality assurance and control are not sufficient to manage the quality characteristics that are significant to each customer. Research into quality management for these environments has been isolated and segmented. No framework exists to holistically manage product quality within an unstable manufacturing environment. This paper seeks to propose a method of holistically managing product quality in a manufacturing environment with high customer input and product variety. The development of a reconfigurable inspection apparatus is discussed as a technological requirement for performing the quality control aspect of the management system.

The quality requirements of modern manufacturing systems were established. The required flow of information for an advanced quality management system was proposed and compared to the information flow in a traditional quality management system. The developed reconfigurable inspection apparatus was tested by performing an inspection of a product configuration within a part family of torches. Commercial products were used for the construction of the apparatus, including the electrical and software aspects. A commercially available simulation package was used to simulate the effects of a random customer order on production flow whilst implementing the developed apparatus.

Modular inspection equipment would prove essential to the implementation of quality control when considering advanced manufacturing environments. An overall management system is also needed for the verification of product quality as per individual customer requirements. Quality needs to be integrated as per TQM principles.

Traditional quality control tools may not always be applicable for unstable market demand. The research indicated the required progression of quality systems to successfully manage the quality for advanced manufacturing. The widespread availability of commercial components for the inspection apparatus verified the shift in supplier focus to meet the needs of shifting manufacturing requirements.

The proposed approach to assure and control quality, as well as the researched inspection apparatus, provided the capability of being implemented in a manufacturing environment that involves production of a variety of products as opposed to being limited to one part family. The use of modular mechanical, electrical and software components will ease the implementation of reconfigurable inspection stations into existing manufacturing setups.

Research indicated that quality systems need to be further developed for assuring and controlling product quality of products with high customer input. No system existed that could holistically consider the quality requirements of a product from design to delivery.

Source errors in a workpiece fixture system include the compliance of the workpiece fixture system and workpiece dynamics. The purpose of this paper is to study the relative significance of these two. The findings would help to achieve computational economy in optimization of fixture layout and/or clamping forces.

Different layouts are generated with the help of a reconfigurable fixture set up and a slot is end milled on the workpiece. Using these data and the finite element software ANSYS, the machining error due to system compliance is computed. The machining error due to workpiece dynamics is obtained using a data acquisition system with the LabView software. These steps are repeated for different clamping forces and the relative contribution of these two sources to the overall machining error is studied.

Results show that the system compliance is much smaller in magnitude compared to workpiece dynamics and hence does not contribute appreciably to the overall machining error. This leads to the conclusion that, for bulky and stiff parts, evaluation of the machining error due to compliance can be done away with.

The paper's originality lies in comparing the two sources of machining error using experimental work and finite element models. To the author's knowledge such a comparison has not been reported in the literature.

The purpose of this paper is twofold. In view of the importance of process platform‐based production configuration (PPbPC) in sustaining product family production efficiency, it is to study the underlying logic for configuring production processes for a product family based on a process platform. Second, it is to apply the Petri nets (PNs) techniques to model PPbPC, in attempting to shed light on the underlying logic.

The authors first identify the fundamental issues in PPbPC, including variety handling, process variation accommodation, configuration at different abstraction levels, and constraint satisfaction. To accommodate the corresponding modelling difficulties, the authors develop a formalism of hierarchical colored timed PNs (HCTPNs) based on the principles of hierarchical PNs, timed PNs, and colored PNs. In the formalism, three types of nets together with a system of HCTPNs are defined to address the modelling of PPbPC.

Applying HCTPNs to vibration motors' case has revealed the logic of specifying complete production processes of final products at different levels of abstraction to achieve production configuration. The preliminary results also further demonstrate the feasibility of modelling PPbPC based on HCTPNs.

Traditional approaches to planning production processes for individual products may limit production performance improvement when companies need to timely produce a high variety of customized products. Systematic methods should be developed to plan production processes for product families so as to achieve production efficiency while utilizing the existing manufacturing resources.

By integrating the advantages of existing PN techniques, the HCTPNs formalism is developed to shed light on planning production processes for product families. The resulting production configuration model can facilitate practitioners to achieve production efficiency in producing large numbers of customized products.

To demonstrate the feasibility of designing a versatile packaging machine for folding cartons of complex geometry and shapes.

The research conducts study of cartons of different geometry and shapes classifying them in suitable types and operations that a machine can understand, conceptualizing a machine that can handle such cartons, modeling and simulation of the machine, and finally design and development of the packaging machine.

It has been shown that such a versatile machine is a possibility; it just needs miniaturization and investment on its development when such machines could be a reality.

This research was aimed at proving the principle, but for practical implementation considerations need to be given for a compact, portable system incorporating sensors.

The design is unique in existence and has been shown to fold cartons of different complexity.

A reconfigurable manufacturing system (RMS) can provide manufacturing flexibility, meet changing market demands and deliver high performance, among other benefits. However, adoption and performance improvement are critical activities in it. The current study aims to identify the important factors influencing RMS adoption and validate a conceptual model as well as develop a structural model for the identified factors.

An extensive review of RMS articles was conducted to identify the eight factors and 47 sub-factors that are relevant to RMS adoption and performance improvement. For these factors, a conceptual framework was developed as well as research hypotheses were framed. A questionnaire was developed, and 117 responses from national and international domain experts were collected. To validate the developed framework and test the research hypothesis, structural equation modeling was used, with software tools SPSS and AMOS.

The findings support six hypotheses: “advanced technologies,” “quality and safety practice,” “strategy and policy practice,” “organizational practices,” “process management practices,” and “soft computing practices.” All of the supported hypotheses have a positive impact on RMS adoption. However, the two more positive hypotheses, namely, “sustainability practices” and “human resource policies,” were not supported in the analysis, highlighting the need for greater awareness of them in the manufacturing community.

The current study is limited to the 47 identified factors; however, these factors can be further explored and more sub-factors identified, which are not taken into account in this study.

Managers and practitioners can use the current work’s findings to develop effective RMS implementation strategies. The results can also be used to improve the manufacturing system’s performance and identify the source of poor performance.

This paper identifies critical RMS adoption factors and demonstrates an effective structural-based modeling method. This can be used in a variety of fields to assist policymakers and practitioners in selecting and implementing the best manufacturing system.

The purpose of this paper is surface roughness prediction using pattern recognition for the aluminium hybrid metal matrix composite (HMMC).

Hybrid composites were manufactured using liquid metallurgy technique. The cast HMMC was machined using an industrial CNC turning centre and the machining vibration signals were acquired using an accelerometer. The acquired signals were processed and used to build a machine learning model for predicting surface finish based on the tool signature.

The authors established a technique for predicting and monitoring the surface quality during machining using a low cost accelerometer. It is capable of being integrated with the machine controller for online warning of deviations in surface roughness. The system is reconfigurable for any machining condition with a very short training period. The use of this model facilitates online surface roughness monitoring, avoiding the need for costly measuring equipment.

The model developed is innovative and not reported widely to the best of the authors' knowledge. The use of accelerometer‐based surface roughness prediction and control is an innovative approach for automation of machining process monitoring. These can be integrated into any existing machining centre as a standalone system or can be integrated into the CNC controller like Fanuc or Siemens.

This paper aims to describe the topic of robot kinematics and provide a modern machine.

The paper examines, in brief, kinematics and robot kinematics, classes, constraints and chains to provide an introduction. An example shows how robot kinematics can benefit the design of advanced machines for industry.

Robot kinematics, in conjunction with mathematics and other disciplines, lead to a greater understanding of robotics design and control.

This paper discusses robot kinematics in brief as a robot design topic in its own right, as well as presenting the Gantry‐Tau robot as a new and interesting kinematic development. As such, the article should be of general interest to robotics engineers and designers.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.

Innovation drives suppliers even as demand is soft. Modular assembly stations, compact part machining/turning systems, linear motor powered motion and smart end effectors lead the way as the industry drives ahead to provide added benefits to users and system integrators.