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Disabled people can be successfully employed in most production processes, provided that one knows how to exploit their abilities and take into account their limitations in order to give them an appropriate job. However, because the level and type of production must be constantly adapted to the needs of the market, the involvement of disabled people in the production process may also change. Additionally, people with disabilities have limitations as well as additional rights that must be considered. As a result, the organisation and planning of their work, side by side with other employees, becomes more complex. Computer simulations can be a support for organising and planning the involvement of employees with disabilities in production processes. The aim of the article is to show how simulations can facilitate the organisation of work of employees with disabilities, with the changing demand for manufactured products. The paper identifies the factors that should be considered, and then presents how the employment of disabled people can affect the operation of the production line and the commercial image of the company. The study uses a combination of System Dynamics and Discrete Event Simulations. The relevant data for the simulation were derived from a production company. [ABSTRACT FROM AUTHOR]

Laser forming is a highly flexible and iterative contactless thermomechanical forming process that utilises a defocused laser beam to induce material shortening and bending. There is a high potential for the use of laser forming in rapid prototyping, small and unique batch production; however, to achieve that potential a certain level of automation is required. The presented work seeks to address this need of automation by proposing an end-to-end sheet-metal manufacturing system utilising laser forming and cutting, where the input for the system is a 3D CAD model and the output is a manufactured product. The contribution of the presented work is interconnected laser forming and cutting framework. The presented framework consists of subsystems for automatic extraction of geometrical information from a CAD model, process planning and generation of manufacturing information, scheduling of tasks and a feedback control loop for laser forming. The framework is experimentally validated and has shown consistent forming and cutting behaviour on two types of parts with variation in cutting features, bend angle and lengths of the bend's free edge. [ABSTRACT FROM AUTHOR]

Purpose: The work aims to assess the impact of the implementation of CNC laser technology on the efficiency and quality of machine parts production, using the example of a company in the metal industry. The introduction of the CNC laser is intended to increase the precision and automation of production processes, which will translate into increased efficiency and quality of manufactured products, in line with the idea of industry 4.0 promoted in the modern economy. Design/methodology/approach: As part of the research, a detailed analysis of the impact of CNC laser implementation on production was carried out, taking into account aspects such as production efficiency, product quality and process optimization. The study used a methodology based on observations of the production process, analysis of technical documentation and interviews with employees involved in the implementation process. Findings: The results of the analysis indicate significant benefits resulting from the implementation of CNC technology, such as shortening production time, increasing the machine utilization rate (OEE) and reducing production waste. At the same time, potential challenges related to the transformation in line with the idea of Industry 4.0 were identified, such as the need to constantly monitor and analyze the effectiveness of the implemented technological solutions. Practical implications: The work is a valuable contribution to the literature on production management and technological innovation in industry. Providing empirical evidence of the benefits of automation and implementation of modern technologies in production processes. Originality/value: The original contribution of this work is the implication of the data on real- world research models. These data allowed the authors to make calculations and indicate directions for design improvements in the machinery sector in line with the promotional idea of industry.4.0. [ABSTRACT FROM AUTHOR]

Welding processes are widely used technologies in the industrial context for creating permanent connections between mechanical components. This popularity is due to their versatility, which arises from the numerous available process variants and the multiple advantages they offer compared to other joining techniques. In the manufacturing context, where devices often operate in extreme conditions, the quality of welds becomes a critical factor in ensuring the safety and reliability of the manufactured products. Furthermore, a sound joint requires careful compliance with the increasingly stringent design specifications demanded by customers who require industry-standard conformity in order to achieve defect-free, robust, and durable welds. To address these needs and to define the optimal roadmap for the investigated process condition, an experimental investigation was conducted on the submerged arc welding process. The experimental trials involved butt joints of ASTM A516 Gr.70 carbon steel plates with different thicknesses in a flat position, utilizing a U-shaped chamfer and a multi-pass welding technique. For each weldment, the effects of the main process parameters on the qualitative characteristics of the manufactured products were evaluated from a metallurgical perspective. This evaluation included an in-depth metallographic analysis of the heat-affected zone of the carbon steel joint and involved both the measurement of the dimensions of these areas as well as the amount of ferrite and pearlite that resulted as the phases observed in the final microstructure of the steel joint following its solidification. Furthermore, the joint quality was assessed with regard to mechanical strength through hardness measurements. By analysing the experimental data, the paper provides a valuable contribution for increasing the productivity of the investigated welding process, while simultaneously meeting the specified industrial quality requirements for the products made of medium-thickness carbon steels. [ABSTRACT FROM AUTHOR]

This study aims to characterise the so-called Sialkoti paper used to produce Pahari drawings preserved today in the Wereldmuseum in Leiden (Netherlands) (WML). These works originate from the Punjab Hills in India (today Himachal Pradesh) and are commonly known as 'Pahari miniature paintings'. The paper upon which these drawings are executed is said to have been produced in Sialkot during the eighteenth and nineteenth centuries when papermaking was an integral part of an overall regional economy correlated with other sectors such as agriculture and the textile industry. Although the term Sialkoti refers to identified papermills in Sialkot (now Pakistan), the paper from this region is yet to be subjected to a systematic study. This article therefore explores the paper(s) in question through macro- and microscopic observations of structure, pulp and fibres. The study of historical sources, complemented by the analysis of paper samples and fibre identification, has revealed that the pulp would have been prepared from a variety of manufactured products using different technologies, such as rags, cloth, mats, rope and other plant-based materials made from local bast fibres which, once tattered, were recycled to prepare the pulp. Microscopic study reveals that a variety of fibre combinations under different conditions and processing steps were used, in particular sunn hemp fibre (Crotalaria juncea L.), a plant species that has until now rarely been identified in historical paper. In addition, the presence of kenaf and jute fibres, as well as a significant quantity of cotton fibres, have also been demonstrated. To overcome the lack of comparative materials, our work was supported by a comparative study of several materials made from sunn hemp now held in the Ethnobotany Collection at Kew Gardens. Samples were taken from these materials and provided useful reference micrographs for the identification of the WML samples. The quality of the paper used by Pahari artists, as well as the raw materials available and their processing, are discussed in detail. Putting all the data, including technical and historical information into perspective, we conclude that the Pahari artists used a paper of inferior quality compared to other types of paper used for other purposes such as the creation of illuminated manuscripts in the Punjab plains. This study therefore provides useful analytical and material evidence that complements previous historical, technical and anthropological studies. [ABSTRACT FROM AUTHOR]

Additive Manufacturing increasingly becomes a viable alternative to conventional manufacturing technologies. However, the knowledge and awareness to achieve a ready-for-manufacturing and quality-ensured design of additively manufactured products are mostly lacking. Knowledge from the manufacturing process on how certain process variables affect the product requirements must already be considered in product design to assure and potentially enhance the quality a priori, thus saving time and cost-intensive iterations. Therefore, this knowledge must be front-loaded as a basis to suitably adapt product and process design simultaneously. This contribution therefore proposes a framework for the simultaneous product and process design synthesis of existing designs by providing insight knowledge about product and process design specific to Fused Layer Modeling. This is achieved via a consolidated ontology-based knowledge representation and its integration in a design environment. Thus, the aim, in contrast to most existing approaches, is to provide this knowledge on a product- and application-specific basis to parallelise product and process design for non-assembly mechanisms and exploit currently unused potential concerning the interaction between the different domains. This can shorten development times and also compensate for a lack of background knowledge in certain areas. A practical use case highlights the general procedure, benefits, and applicability. [ABSTRACT FROM AUTHOR]

The rapidly developing manufacturing industry constantly needs top specialists to ensure sustainability (resource optimisation, production efficiency, sustainable products) and to implement the latest know-how (digitalisation, big data analytics, artificial intelligence). Those requirements, in turn, place higher demands on universities, curricula, teaching staff and, above all, laboratories to teach the concept of a smart factory. TTK University of Applied Sciences (TTK UAS) has come to an understanding that renovation of existing production laboratories is unavoidable. Keeping this in mind, a study needs to be conducted to investigate best practices and strategies to develop a new concept that best suits TTK UAS. In this article, the authors examine how to renovate and update the existing university laboratories (production, measurement, CAD/CAM) using simulation software with a Learning Factory concept in mind while still ensuring research development capability. Using the case-study methodology, factory automation simulation software, and a new pedagogical approach, the TTK UAS industrial engineering laboratories are functioning as a cluster, achieving higher learning and R&D efficiency. [ABSTRACT FROM AUTHOR]

Digital transformation driven by artificial intelligence (AI) allows Industry 4.0 and the internet of things (IIoT) to make significant advancements in automating, controlling, and improving the quality of numerous manufacturing processes. Three-dimensional (3D) surface topography of manufactured products holds important information about the quality of manufacturing processes. Surface topography consists of unique properties, which makes the current monitoring approaches ineffective in identifying local and spatial surface faults. In this paper, we develop a generalised spatially weighted autocorrelation approach based on AI for monitoring changes in products based on their 3D topographic surfaces. We propose two effective algorithms to identify and assign spatial weights to the topographic regions with suspicious characteristics. The normal surface hard thresholding algorithm initially enhances the representation of surface characteristics through binarization, followed by the normal surface connected-component labelling algorithm, which utilises the obtained binary results to identify and assign spatial weights to the suspicious regions. We then introduce a generalised spatially weighted Moran index, which exploits the assigned weights to locally characterise and monitor changes in the spatial autocorrelation structure of identified regions. After an anomaly surface is detected, we extract different fault diagnostic information. The proposed approach proves its robustness and efficiency in characterising, monitoring, and diagnosing different patterns of faults in 3D topographic surfaces. [ABSTRACT FROM AUTHOR]

Control charts are an important part of statistical control because they allow the inspection characteristics of manufactured pharmaceutical products to be tracked and controlled. It helps show current processes and status and, if necessary, identifies areas for further development. The investigation and analysis of an initial trend for a few inspection properties of the manufactured chemical 3-O-ethyl 5-Omethyl 2-(2-aminoethoxymethyl)-4-(2-chlorophenyl)-6-methyl-1,4-dihydropyridine-3,5-dicarboxylate benzenesulfonic acid is the main focus of the current work. Using the well-known commercial SPC platform for comprehensive SPC analyses. The datasets of the assay and polarization rotation followed the Weibull pattern. While the results of the overall impurities and particle size test data were adopted for Gaussian spreading the Johnson family transformation was implemented for the latter. An exploratory Individual-Moving Range plot is the method used to trend the datasets and capacity analyses were conducted in accordance with that method. Improvements are required to enhance the quality of inspection properties at the preliminary steps since there are signs of a low capability process in the particle size test and the assay to some extent. In addition, the means of the quality tests should be brought to the center since the preliminary data are not in the middle of the specification range. Thus, some inspection characteristics are lower quality than others and need immediate correction and enhancement at the initial stages of the establishment of the manufacturing process and criteria. This perspective highlights the importance of control charts in the examination of the quality of chemically manufactured materials. [ABSTRACT FROM AUTHOR]

Purpose: Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system. Design/methodology/approach: This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations. Findings: Density, Young's modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects. Originality/value: To the best of the authors' knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing. [ABSTRACT FROM AUTHOR]

Purpose: Fused deposition modeling (FDM) is an extensively used additive manufacturing method with the capacity to build complex functional components. Due to the machinery and environmental factors during manufacturing, the FDM parts inevitably demonstrated uncertainty in properties and performance. This study aims to identify the stochastic constitutive behaviors of FDM-fabricated polylactic acid (PLA) tensile specimens induced by the manufacturing process. Design/methodology/approach: By conducting the tensile test, the effects of the printing machine selection and three major manufacturing parameters (i.e., printing speed S, nozzle temperature T and layer thickness t) on the stochastic constitutive behaviors were investigated. The influence of the loading rate was also explained. In addition, the data-driven models were established to quantify and optimize the uncertain mechanical behaviors of FDM-based tensile specimens under various printing parameters. Findings: As indicated by the results, the uncertain behaviors of the stiffness and strength of the PLA tensile specimens were dominated by the printing speed and nozzle temperature, respectively. The manufacturing-induced stochastic constitutive behaviors could be accurately captured by the developed data-driven model with the R2 over 0.98 on the testing dataset. The optimal parameters obtained from the data-driven framework were T = 231.3595 °C, S = 40.3179 mm/min and t = 0.2343 mm, which were in good agreement with the experiments. Practical implications: The developed data-driven models can also be integrated into the design and characterization of parts fabricated by extrusion and other additive manufacturing technologies. Originality/value: Stochastic behaviors of additively manufactured products were revealed by considering extensive manufacturing factors. The data-driven models were proposed to facilitate the description and optimization of the FDM products and control their quality. [ABSTRACT FROM AUTHOR]

The most important step in finalizing a production process is precise quality control of the manufactured product. For products manufactured with a high degree of precision, under strict tolerances, precise quality inspection is essential. In modern production, it is desirable for such processes to be accurate, reliable, repeatable, and above all, automated. Our work focuses on the design and development of a measuring cell, that precisely measures the surface roughness, and detects geometrical defects of a smaller workpiece, which was manufactured with a high level of precision and quality. For conducting precise measurements, the apparatus employs only a pair of displacement sensors, that measure a single point on touch-sensitive surfaces, using laser triangulation. Although such sensors are very accurate, their main drawback lies in the fact that they can perform measurements on only a single point. Thus, the measuring cell enables the sensors to move on the x and y axis, while also clamping the workpiece and allowing it to rotate to a desired position. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) optical systems have been recently deployed for the assessment of 3D topography of finished products during manufacturing processes. Although the 3D topographic data contain rich information about the product and manufacturing processes, existing monitoring approaches are incapable of capturing the complex characteristics between the topographic values, which makes them ineffective in detecting local and spatial surface faults. We develop a spatially weighted graph theory-based approach for accurate monitoring of 3D topographic surfaces. We imporove the representation of surface characteristicsby proposing the in-control multi-region surface segmentation algorithm, which segments the observed topographic pixels into clusters according to the information learned from in-control surfaces. We propose the maximum local spatial randomness feature for the effective description of local and spatial topographic characteristics. After representing the surface characteristics as a spatially weighted graph network, we monitor its connectivity through the developed spatial graph connectivity statistic. The proposed approach is robust in detecting and locating different forms of local and spatial faults that appear on simulated and real-life topographic surfaces and outperforms the existing monitoring approaches. [ABSTRACT FROM AUTHOR]

The article presents the results of an analysis of the impact of selected Lean Manufacturing tools on the number of failures occurring on the example of a production plant from the metal industry, specializing in the production of welded pipes. Reducing the failure rate of individual devices on the production line is one of the key factors determining the efficiency of the production process and the quality of the manufactured product. In order to reduce unplanned machine downtime caused by failures, various techniques are introduced to reduce them, for example TPM (Total Productive Maintanance). The purpose of this article is to conduct a statistical analysis to assess the impact of TPM implementation on the number of reported failures on one of the production lines. [ABSTRACT FROM AUTHOR]

Planners and designers of production systems must frequently evaluate the similarities in the manufacturing process of various products to achieve efficient and economical production. The purpose is to reasonably arrange mixed production. The similarity of manufacturing technique processes is an important basis for classifying product manufacturing processes. This study proposes an innovative method based on process constituent elements model to objectively calculate the similarity of product manufacturing processes. Firstly, the similarity model of the manufacturing technique process is established on the basis of six dimensions of process constituent elements, namely, input, output, resource, environment, value-added processing activity and quality control & inspection. Secondly, the characteristics of the six dimensions of the process constituent elements are determined. Corresponding methods are applied to solve the similarity of process constituent elements in each dimension on the basis of the characteristic attributes of process constituent elements of different dimensions. Thirdly, extended interval analytic hierarchy process and quantitative calculation method based on angle information entropy are integrated to determine the weights of dimensions of the six elements. Lastly, the proposed method is applied to the process classification of a group of product manufacturing technique processes, and the feasibility and effectiveness of the method are proven. [ABSTRACT FROM AUTHOR]

Due to the need to use very precise manufacturing processes, hydraulic applications are one of the most demanding parts in production. Such a feature requires using molded and properly machined parts. On the other hand, such an approach makes hydraulic parts very heavy and requires the use of large amounts of material. One of the most promising manufacturing technologies that could be a real alternative to hydraulic parts production is additive manufacturing (AM). This paper aims to study how the AM process affects the performance properties of the as-built state, and investigate changes after different types of postprocessing in the case of hydraulic check valves. Based on the obtained results, using proper postprocessing is a crucial feature of obtaining check valves that perform their functions in a hydraulic system. In as-built parts, the surface roughness of the valve seats significantly exceeds the acceptable range (almost nine times—from 4.01 µm to 33.92 µm). The influence of the surface roughness of the valve seats was verified via opening pressure and internal leakage tests based on ISO standards. The opening pressures in all tested samples were similar to those in the conventionally made counterparts, but in the case of internal leakage only a fully finished AM valve revealed promising results. The obtained results could be useful for various enterprises that are seeking weight reduction possibilities for their low-volume manufactured products. [ABSTRACT FROM AUTHOR]

The quality of counterfeit items has increased dramatically, with modern global manufacturing being able to duplicate the materials, construction, and visual features of items. Detection of fraudulent coinage can parallel authentication of food, beverages, and manufactured goods by studying product‐inherent features. Counterfeit detection is performed by comparing an Example group with a Questioned group. A model is developed for both groups using standard tests on individual pieces. Coin weight is used here as an illustration. The model should also follow the natural science of the system. In this case, the manufacturing process variation is known and steady, and the underlying distribution is known or can be determined from authentic pieces. The proposed detection method uses testing of many individual pieces, then using reverse‐quality‐engineering methods to identify possible sources. This strategy looks at the variation between individual pieces to determine the process capability of a machine, assembly line, or plant to create product consistency for a manufacturer. Fraudulent items may be manufactured within specification, but demonstrate a manufacturing process capability different than that of the authentic manufacturer. In this report, we examine the model previously reported and use reconstruction techniques to re‐create the evidence set to validate the model, increase model accuracy, and confirm the conclusion previously reached, showing that the Questioned set is likely over 37% non‐conforming by weight. In this case, the decision outcome of the analysis was improved by using additional methods not included in the modeling software package originally used. [ABSTRACT FROM AUTHOR]

With the increasing complexity of production systems and manufactured products, operators face high demands for professional expertise and long-term concentration. Augmented reality (AR) can support users in their work by displaying relevant virtual data in their field of view. In contrast to the extensive research on AR assistance in assembly, maintenance, and training, AR support in quality inspection has received less attention in the industrial context. Quality inspection is an essential part of industrial processes; thus, it is important to verify whether AR assistance can support users in these tasks. This work proposes an AR-based approach for quality inspection. For this, pilot AR software was designed and developed. The proposed AR approach was tested with end users. The task efficiency, the error rate, the perceived mental workload, and the usability of the AR approach were analysed and compared to the conventional paper-based support. The field research confirmed the positive effect on user efficiency during quality inspection while decreasing the perceived mental workload. This work extends the research on the potential of AR assistance in industrial applications and provides experimental validation to confirm the benefits of AR support on user performance during quality inspection tasks. [ABSTRACT FROM AUTHOR]

The 3D surface topography of finished products is a key characteristic for monitoring the quality of products and manufacturing processes. The topography has unique properties in which the topographic values are spatially autocorrelated with their neighbours and the locations of topographic values randomly change from one surface to another under the in-control process behaviour, making the online detection of local topographic changes challenging. Due to the complex structure of topographic data, the existing monitoring approaches lack the detection of local changes. Therefore, we develop a novel online monitoring approach for detecting local changes in 3D topographic surfaces. We introduce a multilevel surface thresholding algorithm for enhancing the representation of topographic values by slicing the 3D surface topography into cumulative levels in reference to the characteristics of the in-control surfaces. The spatial and random properties of topographic values are quantified at each surface level through the proposed spatial randomness profile. After obtaining the spatial randomness profile, an effective monitoring statistic based on the functional principal component analysis is developed for detecting anomaly surfaces. The proposed approach shows superior performance in identifying a wide range of fault patterns and outperforms the existing approaches in both simulated and real-life topographic data. [ABSTRACT FROM AUTHOR]

Concurrent configuration of a product and its associated production process is a challenging problem in customer/supplier relations dealing with customisable or configurable products. It gathers in a single model multiple choices and constraints which come simultaneously from products (choices of components or functionalities), from processes (choices of resources and quantities) and from their mutual interrelations. Considering this problem as a Constraint Satisfaction Problem (CSP), the aim of this article is to improve its optimisation, while considering multiple objectives. Using an existing evolutionary optimisation algorithm as a basis, we propose an approach that reduces the computation time required for optimisation. The idea is first to quickly compute a rough Pareto of solutions, then ask the user to select an area of interest, and finally to launch a second computation on this restricted area. After an introduction to the problem, the approach is explained and the algorithm adaptations are presented. Then various computation experiments results demonstrate that computation times are significantly reduced while keeping the optimality level. [ABSTRACT FROM AUTHOR]

Statistical process control plays a significant role in manufacturing industries as processes become more advanced and manufactured products more complex. Because of the increasing sensitivity of the processes and the inadequacy of the methods based on human inspection, use of product images in statistical process control has been considered by some researchers. In this paper, a regression-based method is developed to monitor image data under two-scale analysis. In the first scale, wavelet transformation is used to extract the main features of geometric profile created from the images. The next scale is to monitor the small-scale components which could be expressed by correlation in error terms. To monitor correlation in error terms, a parametric method is developed. Parameters of the parametric model including spatial correlation coefficient and error term variance are estimated using Ordinary Least Squares (OLS) and Generalized Least Squares (GLS) estimators, respectively. After extracting features for both scales, some appropriate test statistics are computed. Then, monitoring the process is performed by plotting these test statistics on corresponding control charts. Performance of the proposed method is evaluated in terms of run length measures and the difference between the actual value and the estimated value of change-points. Simulation studies are performed on tile images, and the results show the capability of the proposed method in detecting out-of-control conditions and estimating the change-point. The results also indicate the proper performance of the proposed method in monitoring industrial processes to detect out-of-control conditions and identifying the source of variability. [ABSTRACT FROM AUTHOR]

This article presents a study with the aim of optimizing a production system, consisting of a machine that produces a single type of parts, that degrades over time. This degradation affects the availability of the deployed machine and increases the defective rate of the manufactured products. The machine is subject to random failures and repairs. It has a defective rate which increases with its degradation. An overhaul of the machine allows to reduce this defective rate and bring it back to its initial condition. The objective of this study is to find a joint policy for production, maintenance and quality control, in order to increase the availability of the machine, improve the quality of the manufactured products and minimize the total cost of production. To achieve this goal, we formulated the research problem and used a stochastic dynamic programming approach to develop the Hamilton-Jacobi-Bellman (HJB) type optimum conditions. Then, we simulated a practical hybrid application to optimize the production of a Router class R CNC cutting machine that transforms polypropylene sheets in a Quebec (Canada) company specialized in the production of fire pumps. The obtained results allowed us to propose a critical threshold production policy, corrective and preventive maintenance strategies, and a sampling type of quality control to the company. Finally, we performed a sensitivity analysis to ensure the validation of the proposed policies. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the research was to present the impact of the use of selected Lean Manufacturing tools (5S and Poka Yoke) on the efficiency of the production process and the number of non-conforming products generated during the manufacturing process. The research was carried out on the basis of data from a production plant in the automotive industry. Design/methodology/approach: The article presents a statistical analysis of the impact of the implementation of Lean Manufacturing tools on the production process - a case study. Findings: The obtained results allowed to present the scale of changes coming in the manufacturing process, confirming at the same time the positive effect of the implementation of Lean Manufacturing tools on the efficiency of the manufacturing process and the quality of manufactured products. As a result of the implementation of the 5S and Poka Yoke tools, an increase in efficiency was found in all production operations. Social implications: The analysis carried out can increase awareness of the importance of the impact of Lean Manufacturing on the production process. Originality/value: In the article, an original statistical analysis was carried out, indicating an increase in the efficiency of the production process due to the implementation of selected Lean Manufacturing tools. [ABSTRACT FROM AUTHOR]

Today's manufacturing systems are becoming increasingly complex, dynamic and connected hence continual prediction of manufactured product quality is a key to look for patterns that can eventually lead to improved accuracy and productivity. Recent developments in artificial intelligence, especially machine learning have shown great potential to transform the manufacturing domain through analytics for processing vast amounts of manufacturing data generated (Esmaeilian et al. in J Manuf Syst 39:79–100, 2016). Although prediction models have been built to predict product quality with good accuracy, they assume that same distribution applies on training data and testing data hence fail to produce satisfying results when machines work under different conditions with varying data distribution. Naïve re-collection and re-annotation of data for each new working condition can be very expensive thus is not a feasible solution. To cope with this problem, we adopt transfer learning approach called domain adaptation to transfer the knowledge learned from one labelled operating condition (source domain) to another operating condition (target domain) without labels. Particularly, we propose an end-to-end framework for cross-machine product quality prediction, which is able to alleviate domain shift problem. To facilitate the cross-machine prediction performance, a systematic feature selection approach is designed and integrated to generate most suitable feature set to characterize the collected data. Comprehensive experiments have been conducted using actual manufacturing data and the results demonstrate significant improvement on cross-machine product quality prediction as compared to conventional techniques. [ABSTRACT FROM AUTHOR]

Effective retention plays an essential role in denture success and the ratio of the dentures' resistance to denture movement towards occlusal direction should be a major consideration. Evaluating and understanding the difference between conventional and Computer Aided Design/Computer Aided Manufacturing (CAD/CAM) systems in terms of the magnitude of the retention force on the approximate surfaces of retention teeth was the aim of this research. From fifty patients diagnosed with partial edentulousness class II, subclass 1, according to Kennedy classification, twenty fulfilled the inclusion criteria and were used as material for 20 master stone models on which the retention strength measurements of the conventional and CAD/CAM removable partial dentures (RPD) were made. The measurement was made with a DO663i dynamometer on 200 denture extractions on conventional and CAD/CAM manufactured dentures. The results were processed with statistical packages SPSS Statistics 22 and EasyFit 5.5. The average value of retention force in the conventional model was 0.027739 N, and in the CAD/CAM model 0.04538271 N. This means that in the CAD/CAM model the mean value of this component is 0.01764 N greater than the same component in the conventional method. The mean value of the normal component of the retention force in the CAD/CAM model is about 64% higher than that of the conventional model. Other researches also indicate that conventional dentures are with lower retention and stabilization than dentures manufactured with CAD/CAM procedures as well as a reduction of unwanted rotations in these dentures. Contemporary CAD/CAM manufacturing of RPD includes precise planning of the retention clasp and guide planes, while framework milling leads to an almost ideal final denture. The superiority of CADCAM technologies and the simplicity of the method, undoubtedly give us an opportunity to apply this system in everyday clinical practice. [ABSTRACT FROM AUTHOR]

Applying the concept of Digital Twin in production processes supports the manufacturing of products of optimal geometry quality. This concept can be further supported by a strategy of finding the optimal combination of individual parts to maximise the geometrical quality of the final product, known as selective assembly technique. However, application of this technique has been limited to assemblies where the final dimensions are just function of the mating parts' dimensions and this is not applicable in sheet metal assemblies. This paper develops a selective assembly technique for sheet metal assemblies and investigates the effect of batch size on the improvements. The presented method utilises a variation simulation tool (Computer-Aided Tolerancing tool) and an optimisation algorithm to find the optimal combination of the mating parts. The approach presented is applied to three industrial cases of sheet metal assemblies. The results show that using this technique leads to a considerable reduction of the final geometrical variation and mean deviation for these kinds of assemblies. Moreover, increasing the batch size reduces the amount of achievable improvement in variation but increases the amount of achievable improvement in the mean deviation. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) is a technology that enables the creation of complex shapes with advanced structural and functional properties. It has transformed the traditional manufacturing operations into a more flexible and efficient process, reshaping the whole value chain and allowing new levels of product customization. AM is a layer‐by‐layer manufacturing process, in which materials are deposited in each layer to create the object of interest. Due to the layer‐wise nature of the process, anomalies and defects might occur within each layer, across several layers or throughout the whole sample. An accurate and responsive detection strategy that enables the detection of various types of anomalies is essential for ensuring the quality and integrity of the manufactured product. In this paper, a hierarchical in situ process monitoring approach, namely, a three level monitoring strategy, is proposed to detect local, layer‐wise, and sample‐wise anomalies using thermal videos acquired during the manufacturing process. The proposed approach integrates hierarchical low‐rank tensor decomposition methods with statistical monitoring techniques to effectively detect anomalies at different levels, namely, the within‐layer level, the layer level, and the sample level. Simulations are used to evaluate the performance of the method and compare with existing benchmarks. The proposed approach is also applied to thermal videos acquired during the laser powder bed fusion (L‐PBF) process to illustrate its effectiveness in practice. [ABSTRACT FROM AUTHOR]

Increasing demand for manufactured goods in industries such as automobiles, electronics, construction, and aerospace has motivated researchers to develop sustainable manufacturing processes. Most metal-forming lubricants are not eco-friendly; they may cause substantial chemical emissions and constitute a community threat. Bio-oil lubricants are seen as possible replacements for mineral oil-based lubricants. Computational modelling of the forging process uses the finite element method to accelerate and improve design. This research intends to act as a case study and demonstrate how friction behaves differently in open-closed forging tests of different palm oil derivatives. The relationship between the different types of friction was studied using a cold forging test in conjunction with the development of a Coulomb–Tresca friction model. From the results, it can be shown that the friction behavior for the closed forging test (CFT) and the ring compression test (RCT) differs; the CFT exhibits a diversified friction adaptation, while the RCT exhibits a single friction adaptation. From both tests, palm stearin (PS) shows the lowest friction behavior where at RCT the friction is estimated at m = 0.10/μ = 0.05 and the CFT has a varied friction and the average friction is estimated at m = 0.352/μ = 0.1626. On the other hand, commercial metal-forming oil (CMFO) shows the highest lubrication sample in friction, where the value of friction is similar to the no lubricant sample (NA-O), which is (m = 0.45/μ = 0.1875) on the RCT test and (m = 0.424/μ = 0.1681) on the CFT test. [ABSTRACT FROM AUTHOR]

Nowadays, manufacturing firms are dealing with the unpredictability of market requirements and the frequent changes induced by technological innovation. For this reason, firms are more and more addressing the need to be responsive at an affordable cost. To do so, they are required to develop a capability called reconfigurability. This paper is a review of the existing literature because the current need makes interesting to reflect on the state of the art of reconfigurability as a concept. This reflection has led to focus on reconfigurability characteristics for both their relevance and their relationships with managerial decisions in manufacturing. To this end, a framework has been proposed. It is based on system lifecycle and production levels. These two elements have been deduced from literature and identified as relevant dimensions for decision-making. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the study was to analyze the phenomena occurring in the industrial area as a result of the penetration and spread of new technologies and innovations within the framework of Industry 4.0, taking into account the possible forms and areas of their application in practice. Design/methodology/approach: The research method was an analysis of the literature on the Fourth Industrial Revolution and our own observation of the changes occurring in the industrial area in the context of new technologies. Findings: Currently, the industrial area and its innovative potential is conditioned by new technologies, which are increasingly (directly and indirectly) influencing production processes and manufactured products, while implying their continuous evolution. The study reveals a research gap regarding the lack of systematic research - analysis in the field of the degree and depth of the changes that have occurred, in which the products of the fourth industrial revolution affect the achievement of the adopted goals within the industrial sector and sustainable development. Research limitations/implications: Future research directions will concern the scope of implications of Industry 4.0 creations in the industrial and service sectors and their impact on the operation of business entities. Another direction of research will be the question of the validity of the division of economic sectors in view of the significant interpenetration of the material, product and service spheres. Practical implications: The results of the research indicate the possibilities of implication of Industry 4.0 creations (such as, but not limited to: advanced human-machine interfaces, Internet of Things platforms, intelligent sensors, cloud computing, 3D printing, mobile devices, data analytics and advanced algorithms, multifaceted customer interactions and their profiling) in order to increase the efficiency of processes implemented in manufacturing companies and increase their level of competitiveness. Originality/value: Filling the research gap in the analysis of creations and improvements in the industrial area resulting from the diffusion of new technologies and innovations under Industry 4.0 and the possibilities of their implications. The research is addressed to the management of business entities. [ABSTRACT FROM AUTHOR]

The subject of this article was connected with the problem of finding an effective layout of manufacturing mechanisms in a particular manufacturing hall in DELTA Company, where we were part of a project team. The project team's goal was to solve the problem associated with the actual layout with the help of modelling and designing. It was necessary to analyse the actual layout and also opinions and possibilities of changes in this particular manufacturing mechanism. It is the manufacturing hall. For the analysis of the actual layout, we decided to work with different analytical methods because there were a lot of elements in this manufacturing system which have their own characteristics that are also connected itself or with others. It was necessary to look at all of these characteristics and their connections, and the result will be based on a prime scheme model of design variations for finding an effective layout of manufacturing mechanisms for a particular hall in DELTA Company. [ABSTRACT FROM AUTHOR]

Fused Deposition Modelling (FDM) is an actively growing additive manufacturing (AM) technology due to its ability to produce complex shapes in a short time. AM, also known as 3-dimensional printing (3DP), creates the desired shape by adding material, preferably by layering contoured layers on top of each other. The need for low cost, design flexibility and automated manufacturing processes in industry has triggered the development of FDM. However, the mechanical properties of FDM printed parts are still weaker compared to conventionally manufactured products. Numerous studies and research have already been carried out to improve the mechanical properties of FDM printed parts. Reinforce polymer matrix with fiber is one of the possible solutions. Furthermore, reinforcement can enhance the thermal and electrical properties of FDM printed parts. Various types of fibers and manufacturing methods can be adopted to reinforce the polymer matrix for different desired outcomes. This review emphasizes the fiber types and fiber insertion techniques of FDM 3D printed fiber reinforcement polymer composites. A brief overview of fused deposition modelling, polymer sintering and voids formation during FDM printing is provided, followed by the basis of fiber reinforced polymer composites, type of fibers (synthetic fibers vs. natural fibers, continuous vs. discontinuous fiber) and the composites' performance. In addition, three different manufacturing methods of fiber reinforced thermoplastics based on the timing and location of embedding the fibers, namely 'embedding before the printing process (M1)', 'embedding in the nozzle (M2)', and 'embedding on the component (M3)', are also briefly reviewed. The performance of the composites produced by three different methods were then discussed. [ABSTRACT FROM AUTHOR]

The Manufacturing Processes course includes the main principles of the processes, engineering materials, tools, machines, and examples of manufactured goods. Transferring the up-to-date knowledge to the students may change over time although core topics remain the same. This paper aims to attract attention to the need for change to obtain a well-prepared course content that combines theory and practice. For this purpose, the study is structured in two phases. In the first phase, teaching and grading activities for an Industrial Engineering undergraduate course is considered for nine years period. Statistical analysis confirm that workshop sessions have a positive effect on students' success. To identify the overall learning experience during the course and the awareness of flipped classrooms, a feedback questionnaire is conducted in the second phase. The questionnaire results verify that students can benefit from audio-visual course materials that are shared with them before the class. Case discussions and hands-on practices may be helpful to increase the success of undergraduate engineering students for courses like Manufacturing Processes. However, strict health-safety regulations and unexpected occasions such as pandemics may restrict hands-on learning. Learning environments equipped with new technologies can replace traditional methods soon when it is not possible to conduct such training physically. [ABSTRACT FROM AUTHOR]

Plug-assist thermoforming is a complex process with numerous parameters influencing the quality of the manufactured product. The pre-stretching stage is the most important step in plug-assist thermoforming. Mechanical pre-stretching is used to redistribute material from thicker regions to thinner ones with a plug-assist tool. Experimental tests do not assess all potentially relevant influences. Numerical simulations are therefore useful to achieve a deeper understanding of the process and the mutual interactions between the input parameters. In this paper, we develop thermoelastoviscoplastic polymer behavior and thermomechanical friction finite element models to simulate the plug-assist pre-stretching of high-impact polystyrene, amorphous polyethylene terephthalate, and lightweight polystyrene sheets. The effects of plug-assist tool materials and process conditions are experimentally and numerically analyzed. Plug pre-stretching force and thickness distribution of the simulated test match well with the measured results. The proposed models accounting for the main thermomechanical aspects of the plug-assist thermoforming process provide a way to predict the quality of thermoformed parts. [ABSTRACT FROM AUTHOR]

The article discusses the possibilities of introducing selected aspects and problems in the robotization of the workstation in the hot die forging process, the production of the yoke forging carried out on a crank press in a manual system. The implementation of the developed solution was performed to increase the production efficiency without lowering the quality and mechanical parameters of the produced forgings and with preserved durability of the forging instrumentation. The conducted investigations included numerous aspects of the whole process line, with a special consideration of the adjustment of the currently realized technology to the working conditions of the robots in reference to the ejector system ensuring proper collection and relocation of the forgings by the manipulator grippers in the consecutive operations. The conduct also included the selection and localization of the robots and the grippers solutions, as well as the changes in the tool construction aiming at adjusting it to the gripper pins as well as collecting the hot charge material from the heater. Implementing robotization into one of the most difficult production processes aimed at replacing the role of a human by transferring the competences from the operator of the die forging process onto a supervising person, where all the activities are realized automatically, thus eliminating the effect of the human factor on the quality of the manufactured product. Additionally, the robotization of the forging process brought a lot of tangible benefits, such as stability and repeatability of the process (reduction of reject rate), as well as increased efficiency and quality of the forgings. [ABSTRACT FROM AUTHOR]

The article describes the DGSZM one4all sports mouthguard of the German Society for Sports Dentistry (DGSZM). This mouthguard meets the minimum requirements for a mouthguard manufactured according to sports dental criteria, including individual production, maximum protection of the teeth and jaw, high wearing comfort, and cushioning function. The mouthguard is continuously being developed and has already met all criteria for several years. The DGSZM aims to certify the mouthguard and offers international courses in collaboration with other organizations. The mouthguard is made of pre-laminated, three-layered splint material and is manufactured by the company Erkodent. The article describes the production of a high-quality sports mouthguard using recommended materials and devices. Through numerous optimizations, the production effort could be reduced, so it is no longer necessary to rely on industrially manufactured products. The mouthguard offers high protection and has a volume of less than 5 ml. The production takes place in several steps, with the outer layers being removed and the mouthguard being individually adjusted. The importance of sports dentistry and individually manufactured mouthguards is emphasized, and the German Society for Sports Dentistry takes a pioneering position in this field. [Extracted from the article]

In this paper, we address a model for supply chain coordination. There are m manufacturers modelled as single machines, each of which processes a specific set of jobs (products). After processing is completed, jobs are batched, and batches are shipped to a customer by means of vehicles. The problem consists in concurrently finding a production schedule of the jobs, a partition of jobs into delivery batches and an assignment of delivery batches to vehicles, so that jobs are delivered within their deadlines and total costs are minimised. We focus on a scenario characterised by fixed departure times and inventory holding costs. For each departure time there is a given number of vehicles, possibly having limited capacity. Each job incurs a cost proportional to the time from job completion to delivery departure. In this paper, we show that the problem is NP-hard even for a very restricted case, and report various polynomiality results for two scenarios, namely: (i) when the production sequence of each manufacturer is fixed in advance, and (ii) when there is a single manufacturer and processing times are all equal to 1. We also point out several open problems. [ABSTRACT FROM AUTHOR]

Additive manufacturing technology has been evolving for several years. New material options, better processing speeds and greater autonomy are some of the characteristics of this technology that are still under research. However, in its current state, many commercially available 3D printers are competing with traditional manufacturing techniques in the fabrication of enduse products. In this paper, different additive manufacturing technologies are compared with injection moulding in a real-world case study. The comparison is conducted in terms of lead time and total production cost. From the case under study, it becomes obvious that none of the additive manufacturing technologies examined is yet able to practically replace injection moulding for medium- and high production volumes. However, when considering low-volume production, both rapid tooling and additive manufacturing may offer an alternative that could result into shorter lead times and decreased total production costs. In addition, the introduction of Additive Manufacturing in a producer's production portfolio can increase flexibility, reduce warehousing costs and assist the company towards the adoption of a mass customisation business strategy. [ABSTRACT FROM AUTHOR]

Notwithstanding the interest it elicits from academics and practitioners, relatively little is known about the market for remanufactured products. Research, still in its infancy, has focused almost entirely on what affects willingness to pay, and our understanding of other key marketing questions, such as what drives search intensity for remanufactured products and the number of remanufactured products on offer, is limited. This paper fills this knowledge gap. Focusing on the online market for remanufactured electrical and electronic products, we empirically test whether product-specific and market-specific determinants affect search intensity and number of remanufactured products on offer, that is number of listings. We use as inputs online search traffic, product-specific data collected from various other online sources and relevant eBay listing data. Our analysis supports the hypotheses that search intensity for remanufactured products is associated with search intensity for price and elapsed time since the launch of new counterpart products. Number of remanufactured products listed is associated with number of listings for new counterparts and two product-specific characteristics: presence of moving parts and whether the product is used for personal hygiene. We discuss several implications of our findings for remanufacturers and policy-makers as well as directions for future research. [ABSTRACT FROM AUTHOR]

In this work, an innovative methodology to improve the Supply Scrap Management Process (SSMP), based on Value Stream Mapping (VSM), is presented. VSM is one of the best tools to map a process and eliminate its critical issues, that produces good results if applied to production processes, but can be ineffective for management processes as the SSMP. Therefore, the main objective of this work is to overcome this limitation. The proposed approach taking the name Scrap Value Stream Mapping (S-VSM) and integrates concepts from VSM and other Lean Production (LP) and World Class Manufacturing tools. It is structured in five steps. The definition of the process borders and the identification of categories of loss through the first four steps of Cost Deployment is the first step. Then, the SSMP is subdivided in its Accounting and Physical Streams and the current state is drawn. Next, wastes and critical issues are analysed and their root causes are determined using some of LP tools. In step four, improvements are proposed and the future state is drawn. Furthermore, potential savings, in terms of €, are estimated. In the last step, a methodology to monitor the effects of implemented improvements is defined. A case study taken from the application of the S-VSM within automotive company is presented. [ABSTRACT FROM AUTHOR]

We consider how a manufacturer's product variety decision is affected by its distribution strategy. While offering product varietywill generally lead to higher demand, it also has negative implications on production costs and demand uncertainty.We investigate how the manufacturer's optimal product variety decision differs when selling directly to customers (centralised scenario) as compared to selling through a retailer (decentralised scenario). We find that the retailer's power and the impact of product variety on demand significantly affect the attractiveness of product variety and determine under which distribution strategy the manufacturer should provide a higher level of variety. [ABSTRACT FROM AUTHOR]

This paper examines the effect of forward channel competition and power structure on dual-channel closed loop supply chains (CLSC), which consists of a manufacturer, a retailer and a collector. The manufacturer can either wholesale products to the retailer or directly sell them to the market, the collector undertakes the collection activity of used products. Under different channel power structures, a centralised and three decentralised models are explored under symmetric and asymmetric relative status between direct and retail channels. Through a comprehensive comparison among these models, the result shows that each channel member has an incentive to play the channel leader's role. Meanwhile, from the total channel system's perspective, we find that the manufacturer-led or retailer-led model can either be the most effective CLSC under symmetric relative channel status, which depends on the channel substitution rate between two channels. While under asymmetric relative channel status, the numerical result shows that the whole CLSC should select collector-led, manufacturer-led and retailer-led CLSC model in turn with the retail channel's relative status becoming stronger. Finally, with the benchmark of the centralised decision-making system, we design modified two-part tariff contracts to coordinate dual-channel CLSCs under different channel power structures. [ABSTRACT FROM AUTHOR]

A feasible constant work in process (CONWIP) policy can guide developer to better implement CONWIP system. The feasible policy should be selected from alternatives by evaluation. Therefore, how to generate more than one CONWIP alternative policy to evaluate is an inevitable problem in CONWIP practice. From the perspective of loop structure, we propose CONWIP design framework (CDF) which is a systematic design approach to obtain CONWIP alternative policies. The basic concepts and components for CDF are discussed in this paper. Based on CDF, we make 10 CONWIP alternative policies for hybrid flow shop in one-of-a-kind production environment, and these alternative policies are evaluated by simulation. The simulation result implies that (i) the CONWIP alternative policy with robustness has the potential to cope with more fluctuations in high-variety production environment; (ii) a better design for CONWIP policy will be able to enhance the system performance in practice; and (iii) the loop structure can serve as a parameter of CONWIP. [ABSTRACT FROM AUTHOR]

To date, research has mainly discussed the definition and classification of producer services. Yet many companies require an integrated solution of products and producer services. The aim of this paper is to propose a model of the ecological evolution of manufacturing service systems (MSS) driven by service providers. This model adopts modular thinking to integrate dispersive producer services into an entire MSS, the process of which forms the ecological evolution of MSS. This paper applies ecological theory to build the ecological evolution mechanism of MSS. In this mechanism, the predator-prey relationship is used as a metaphor for the relationships between manufacturers and service providers in a MSS. A predator-prey model is built to simulate the ecological evolution of MSS. A predation cellular genetic algorithm is adopted to optimise this evolution. The proposed model and algorithm are demonstrated and validated by a case study of MSS in bicycle industry. This study contributes to theory by proposing and clarifying the mechanism for provision of services between businesses. The future research will focus on the application and empirical analysis of this mechanism derived from big data. [ABSTRACT FROM AUTHOR]

Manufacturing processes such as casting, rolling, forging, extrusion, material removal processes, etc. are some of the common techniques used today in manufacturing industries. However, these processes must be carried out with utmost precision and precaution. Even the slightest negligence can give rise to anomalies which can be classified as defects or discontinuities depending upon their repairability. Non-Destructive Testing or NDT is amode of testing which has been adopted by industries for decades to test mass manufactured products for anomalies. This paper discusses various NDT methods, such as Visual Testing, Magnetic Particle Inspection, Penetrant Testing, Ultrasonic Testing, Radiographic Testing, Acoustic Emission and Eddy Current Testing. The paper also discusses how technical advancements have broadened the scope of NDT even in industries that may not be manufacturing oriented, indicating that NDT is not limited to detection of anomalies. Even though these developments have made NDT more favourable, this paper highlights the fact that these techniques are mostly manual and heavily dependent upon inspectors' knowledge and experience, leaving room for errors. This paper also discusses the key challenges and future scope in the field of NDT. [ABSTRACT FROM AUTHOR]

Research Summary: We examine how and when integration of process and product components within a firm's innovation portfolio increases firm returns. Strategy literature argues that integration enhances the firm's appropriation of returns from innovations. We evaluate this argument recognizing that integration is but one of multiple appropriation tools; firms can also use other (e.g., scale‐based) mechanisms to enhance appropriation. Using new measures of integration based on textual coding of patent claims, we demonstrate that while higher process–product integration improves firm performance, this effect diminishes when the firm has greater production capacity or access to markets. Further, high integration lowers innovative productivity. Together, these demonstrations explain why firms, even with awareness of the benefits of integration between components, may not all choose high‐integration strategies. Managerial Summary How should a manager design, structure, and organize the firm's innovation portfolio—as a collection of separate standalone process and product innovations, or a set of innovations each containing both new process and product attributes? Using data from the global chemicals industry and new textual‐coding‐based measures, we demonstrate that the latter helps the firm appropriate returns to its innovations by making it harder for others to understand and replicate its innovations, but that it comes with a tradeoff of lower innovative productivity. We stress that latter approach is less useful when the firm has other scale‐based tools in place, that enhance appropriation as well, such as large production capacity or reach to markets. [ABSTRACT FROM AUTHOR]

Digital Twin is one of the fundamental enabling technologies for Industry 4.0 as it allows the convergence between a physical system and its digital representation. A proper modelling method is the prerequisite for successful digital twin implementation. The manufacturing process determines critically the quality of the manufactured products. The influential elements need to be systematically organized when modelling a manufacturing process. This paper proposes a semantic modelling method named RMPFQ (Resource, Material, Process, Function/Feature, Quality) aiming to interlink the main influential factors related to product quality during manufacturing processes. The proposed RMPFQ model is formalized with an application ontology following the IOF-Core middle-level and BFO top-level ontologies. Based on this ontology, a semantic-driven digital twin architecture is designed and mapped to the recently proposed Cognitive Digital Twin concept. A correlation matrix is designed to quantify the relationships among RMPFQ elements thus to facilitate the industrial applications. A case study based on the assembly process of a washing machine is conducted to demonstrate the implementation procedures of the proposed RMPFQ method. [ABSTRACT FROM AUTHOR]