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The purpose of this paper is to propose an integrated approach for assessing the sustainability of production and simplifying the improvement tasks in complex manufacturing processes.

The proposed approach has been investigated the integration of value stream mapping (VSM), analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). VSM is used as a basic structure for assessing and improving the sustainability of the manufacturing process. AHP is used for weighting the sustainability indicators and TOPSIS for prioritizing the operations of a manufacturing process regarding the improvement side.

The results carried out from this study help the managers’ staff in organizing the improvement phase in the complex manufacturing processes through computing the importance degree of each indicator and determining the most influential operations on the production.

The major limitations of this paper are that one case study was considered. In addition, to an average set of sustainability indicators that have been treated.

The novelty of this research is expressed by the development of an extended VSM in complex manufacturing processes. In addition, the proposed approach contributes with a new improvement strategy through integrating the multi-criteria decision approaches with VSM method to solve the complexity of the improvement process from sustainability viewpoints.

The purpose of this paper is to describe new methods to manage variation in complex manufacturing process chains and to show synergies between the variation risk management (VRM) and six‐sigma approaches.

The research methodology was experimental prototyping conducted in collaboration with industry partners. A prototype IT system was developed and tested to implement the approach. A quality cost‐based system was used to assess variation at each operation stage, for every product characteristic.

A comprehensive approach to the management of manufacturing variation is introduced, based on a new process risk matrix which can be used to specify an individual variation risk for every manufactured characteristic, throughout a manufacturing process chain. The approach has been implemented in a prototype software system and is aimed at the complex products such as those manufactured by the aerospace industry.

The IT approach described was developed during the research and is not commercially available.

Manufacturing industry should be able to use this approach, in particular the process risk matrix concept, to develop more effective management of product variation and resultant cost, in complex process chains.

The paper describes a novel approach to combine VRM and six‐sigma concepts, and introduces the process risk matrix as a structure to understand process variation.

This paper aims to propose a new concept of product manufacturing mode which takes physical manufacturing theory as the basic starting point. In this work, the authors intend to systematically define the basic connotation and extension of physical manufacturing, and sort out the typical characteristics of physical manufacturing, in order to propose the general concept of physical manufacturing.

How to study the combination of physics, mathematics, mechanics and other disciplines with the manufacturing disciplines, and how to elevate modern manufacturing science to a new height, has always been a problem for scientists in the field of manufacturing and engineering construction people to deeply think about. Therefore, on the basis of tracing the development of physics and combining the attributes and functions of manufacturing, the authors propose the basic concept of physical manufacturing. On this basis, the authors further clarify the connotation and extension, theoretical basis and technical system of physical manufacturing, reveal the basic problem domain of research and construct the theoretical foundation of physical manufacturing research, which are of great theoretical value and practical significance to adjust and optimize the manufacturing industry structure, improve the quality of manufacturing industry development and promote the green development of manufacturing industry.

The research on the basic theory and technical system of physical manufacturing will therefore broaden the way of thinking and make a better understanding of manufacturing science and technology, which will promote the development of manufacturing industry to some extent.

On the basis of continuous improvement of the basic theory and conceptual system of physical manufacturing, the physical manufacturing technology will become more and more perfect; physical manufacturing system and intelligent manufacturing system will become the mainstream of next-generation manufacturing system.

The topology of manufacturing systems is specified during the design phase and can afterwards only be adjusted at high expense. The purpose of this paper is to exploit the availability of large-scale data sets in manufacturing by applying measures from complex network theory and from classical performance evaluation to investigate the relation between structure and performance.

The paper develops a manufacturing system network model that is composed of measures from complex network theory. The analysis is based on six company data sets containing up to half a million operation records. The paper uses the network model as a straightforward approach to assess the manufacturing systems and to evaluate the impact of topological measures on fundamental performance figures, e.g., work in process or lateness.

The paper able to show that the manufacturing systems network model is a low-effort approach to quickly assess a manufacturing system. Additionally, the paper demonstrates that manufacturing networks display distinct, non-random network characteristics on a network-wide scale and that the relations between topological and performance key figures are non-linear.

The sample consists of six data sets from Germany-based manufacturing companies. As the model is universal, it can easily be applied to further data sets from any industry.

The model can be utilized to quickly analyze large data sets without employing classical methods (e.g. simulation studies) which require time-intensive modeling and execution.

This paper explores for the first time the application of network figures in manufacturing systems in relation to performance figures by using real data from manufacturing companies.

Manufacturing errors, which will propagate along the assembly process, are inevitable and difficult to analyze for complex products, such as aircraft. To realize the goal of precise assembly for an aircraft, with revealing the nonlinear transfer mechanism of assembly error, a set of analytical methods with response to the assembly error propagation process are developed. The purpose of this study is to solve the error problems by modeling and constructing the coordination dimension chain to control the consistency of accumulated assembly errors for different assemblies.

First, with the modeling of basic error sources, mutual interaction relationship of matting error and deformation error is analyzed, and influence matrix is formed. Second, by defining coordination datum transformation process, practical establishing error of assembly coordinate system is studied, and the position of assembly features is modified with actual relocation error considering datum changing. Third, considering the progressive assembly process, error propagation for a single assembly station and multi assembly stations is precisely modeled to gain coordination error chain for different assemblies, and the final coordination error is optimized by controlling the direction and value of accumulated error range.

Based on the proposed methodology, coordination error chain, which has a direct influence on the property of stealthy and reliability for modern aircrafts, is successfully constructed for the assembly work of the jointing between leading edge flap component and wing component at different assembly stations.

Precise assembly work at different assembly stations is completed to verify methodology’s feasibility. With analyzing the main comprised error items and some optimized solutions, benefit results for the practical engineering application showing that the maximum value of the practical flush of the profiles between the two components is only 0.681 mm, the minimum value is only 0.021 mm, and the average flush of the entire wing component is 0.358 mm, which are in accordance with theoretical calculation results and can successfully fit the assembly requirement. The potential user can be the engineers for manufacturing the complex products.

The aim of this study was to examine how manufacturing digitalization can be leveraged to promote green innovation in the digital era by investigating the effects of manufacturing digitalization on green process innovation, and thus firm performance. The authors also explored how the role of manufacturing digitalization varies with horizontal information sharing, vertical bottom-up learning and technological modularization.

Five hypotheses were examined by performing regression analyses on survey data from 334 manufacturing firms in China.

Manufacturing digitalization positively affects green process innovation, and thus firm performance. Furthermore, this positive effect is strengthened by horizontal information sharing and technological modularization and weakened by vertical bottom-up learning.

This study extends the literature rooted in the natural-resource-based view by identifying the crucial role of green process innovation and investigating the value of manufacturing digitalization for developing green capabilities in the digital era. It also contributes to this line of research by revealing contingent factors to leverage manufacturing digitalization from the information processing perspective. Furthermore, this study extends information processing theory to the digital context and identifies the interaction of organizational design (vertical bottom-up learning and horizontal information sharing) and digital investment (manufacturing digitalization).

Overview All organisations are, in one sense or another, involved in operations; an activity implying transformation or transfer. The major portion of the body of knowledge concerning operations relates to production in manufacturing industry but, increasingly, similar problems are to be found confronting managers in service industry. It is only in the last decade or so that new technology, involving, in particular, the computer, has encouraged an integrated view to be taken of the total business. This has led to greater recognition being given to the strategic potential of the operations function. In order to provide greater insight into operations a number of classifications have been proposed. One of these, which places operations into categories termed factory, job shop, mass service and professional service, is examined. The elements of operations management are introduced under the headings of product, plant, process, procedures and people.

In the last decade, cloud manufacturing (CMfg) has attracted considerable attention from academia and industry worldwide. It is widely accepted that the design and analysis of cloud manufacturing architecture (CMfg-A) are the basis for developing and applying CMfg systems. However, in existing studies, analysis of the status, development process and internal characteristics of CMfg-A is lacking, hindering an understanding of the research hotspots and development trends of CMfg-A. Meanwhile, effective guidance is lacking on the construction of superior CMfg-As. The purpose of this paper is to review the relevant research on CMfg-A via identification of the main layers, elements, relationships, structure and functions of CMfg-A to provide valuable information to scholars and practitioners for further research on key CMfg-A technologies and the construction of CMfg systems with superior performance.

This study systematically reviews the relevant research on CMfg-A across transformation process to internal characteristics by integrating quantitative and qualitative methods. First, the split and reorganization method is used to recognize the main layers of CMfg-A. Then, the transformation process of six main layers is analysed through retrospective analysis, and the similarities and differences in CMfg-A are obtained. Subsequently, based on systematic theory, the elements, relationships, structure and functions of CMfg-A are inductively studied. A 3D printing architecture design case is conducted to discuss the weakness of the previous architecture and demonstrate how to improve it. Finally, the primary current trends and future opportunities are presented.

By analyzing the transformation process of CMfg-A, this study finds that CMfg-A resources are developing from tangible resources into intangible resources and intelligent resources. CMfg-A technology is developing from traditional cloud computing-based technology towards advanced manufacturing technology, and CMfg-A application scope is gradually expanding from traditional manufacturing industry to emerging manufacturing industry. In addition, by analyzing the elements, relationships, structure and functions of CMfg-A, this study finds that CMfg-A is undergoing a new generation of transformation, with trends of integrated development, intelligent development, innovative development and green development. Case study shows that the analysis of the development trend and internal characteristics of the architecture facilitates the design of a more effective architecture.

This paper predominantly focuses on journal articles and some key conference papers published in English and Chinese. The reason for considering Chinese articles is that CMfg was proposed by the Chinese and a lot of Chinese CMfg-A articles have been published in recent years. CMfg is suitable for the development of China’s manufacturing industry because of China’s intelligent manufacturing environment. It is believed that this research has reached a reliable comprehensiveness that can help scholars and practitioners establish new research directions and evaluate their work in CMfg-A.

Prior studies ignore the identification and analysis of development process and internal characteristics for the current development of CMfg-A, including the main layers identification of different CMfg-As and the transformation process analysis of these main layers, and in-depth analysis of the inner essence of CMfg-A (such as its elements, relationships, structure and functions). This study addresses these limitations and provides a comprehensive literature review.

The purpose of this paper is to propose that the effectiveness of organizational design-manufacturing integration (ODMI) practices is contingent upon the degree of complexity of the manufacturing environment. The paper submits that the level of use of ODMI ought to match the level of complexity of the manufacturing environment. The paper puts forward the hypothesis that when a misfit occurs between ODMI and complexity (high use of ODMI practices in low complexity environments or low use of ODMI practices in high complexity environments) manufacturing operational performance declines.

The paper tests the hypothesis based on a survey database of 725 manufacturers from 21 countries. The measurement model was assessed with confirmatory factor analysis and the hypothesis was tested with linear regression.

A misfit between the level of ODMI use (job rotation and co-location) and manufacturing complexity (product and process complexity) has a negative effect on manufacturing operational performance dimensions of quality, delivery and flexibility. Post hoc analyses also suggest that firms that operate in different environments in what concerns the rate of change in process technologies suffer differentiated negative impacts of ODMI-complexity misfit.

Future studies could extend this research to other dimensions of design-manufacturing integration, such as technological practices.

Manufacturers with high levels of complexity should invest strongly in ODMI practices. However, manufacturers with low levels of complexity should invest in these practices with caution since the expected payoffs may not outweigh the effort.

The study assesses fit as a simultaneous set of contingency factors, applying profile-deviation analysis to ODMI and operational performance relationships. By focusing on plant-level manufacturing complexity, this study complements existing studies of product development complexity which tend to focus on project-level complexity.

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.