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High risk is one of the most prominent characteristics of the Chinese construction industry, and it poses a significant threat to construction projects. Owing to initiatives aimed at achieving high efficiency, low carbon emissions, etc., industrialization of the construction industry has become an inevitable trend in China. However, it remains to be discussed whether industrialization of construction can reduce the risks entailed in construction projects compared with traditional construction. The paper aims to discuss these issues.

Based on the theory of risk life cycle, this paper proposes a practical risk assessment technique to assess the risk life cycle, including the risk occurrence time and potential financial losses. This technique is then applied to assess the differences between the risks involved in an engineering, procurement and construction (EPC) project executed via traditional and industrial production modes.

The results show that the total duration of risks in the industrial construction project is half of that in the traditional project. In addition, the expected financial loss entailed in the industrial construction project is 29 percent lower than that in the traditional construction project. Therefore, industrial construction has the potential to optimize risk performance.

There is no significant difference between the traditional and industrial construction models in terms of probability of risk. The maximum total loss might occur in the procurement stage in the case of industrial production, and in the construction stage in the case of traditional production. Moreover, the total expected loss from risk in the EPC project in the industrial production mode is only half of that in the traditional production route. This study is expected to provide a new risk evaluation technique and promote an understanding of the life cycle of risk management in the construction industry.

The purpose of this paper is to explore the key performance indicators (PIs) that serve as a decision support tool in case of dairy supply chain practices and to analyze their interactions in the context of Indian dairy industry sector. A total of 11 PIs have been identified through the literature review and the opinions of an expert team consisting of managerial and technical experts from dairy industry and academics.

A solution methodology based on the interpretive structure modeling (ISM) technique is used to analyze the interactions among PIs and to propose a structural model. The developed model not only helps in understanding the contextual relationship among the PIs, but also in determining their interdependence to assess the supply chain performance in dairy industry. Further, the importance of PIs has been determined based on their driving and dependence power by using MICMAC analysis.

The ISM-based model suggests four PIs at first level, three PIs at second level, one PI at third level as well as one PI at fourth level and two PIs at fifth level. Model allocates to the effective information technology, brand management, responsiveness in shipment and accuracy and a control over wastages as the key PIs in the dairy industry sector. The effective traceability systems, cold chain infrastructure, quality management and the support for technological innovations are the next major PIs. There exists no autonomous PI in MICMAC analysis which proves the importance of identified PIs in the case study.

The proposed model is an attempt to capture the dynamics of milk processing sector and to incorporate all relevant constraints related to internal and external environments that would significantly improve the supply chain performance in the dairy industry.

The model developed in this study has been tested in the cooperative milk processing units based in India and also discussed with the experts from academics. This work may help practitioners, regulators and dairy industry professionals to focus their efforts toward achieving high performance by the effective implementation of the identified PIs.

In this study, 11 PIs are considered. Interactions among PIs are evaluated with the help of the ISM matrix. Out of the 11 PIs, six demonstrate both strong driving and dependence power as explained in the MICMAC analysis.

The purpose of this paper is to investigate the dimensions of TQM, analyse interrelationships and their combined influence on results achieved in ISO certified engineering institutes in India.

This study is based on the questionnaire survey of a sample of 216 faculty members serving in various ISO certified institutes of southern states of India. The data were obtained using a questionnaire that is in line with the self‐assessment philosophy of European Foundation for Quality Management Excellence Model (EFQM). The dataset was subjected to exploratory factor analysis using SPSS17.0 program for Windows. The confirmatory and causal analyses were carried out using AMOS 16.0 software.

The factor analysis confirmed the existence of ten important dimensions of TQM that guide ISO institutes in their quality journey. Structural equation modelling was used to validate the developed TQM model. Leadership of top management was the main driving force for establishing an effective quality management system (QMS) in engineering institutes.

The main limitation is related to the notion of causality. The study has considered perception data for the predictive analysis.

The paper unfolds ten important TQM factors that need attention from education administrators to manage quality in engineering education. The six enablers of the proposed TQM model significantly influence result criteria. The results obtained in this study encourage academic leaders to implement TQM concepts in their institutes to achieve a higher level of stakeholder satisfaction.

The paper is a new contribution to broad understanding of TQM concepts and their impact on performance measures in engineering education in India.

This paper proposes a new metric, named Operational Space Efficiency (OpSE), intended to diagnose and quantify the inefficient use of floor space for stocking materials in industrial workstations. OpSE presents a formulation analogous to the well-known Overall Equipment Effectiveness and can be obtained as the product of three distinct indicators: Standard Compliance Effectiveness, Standards Selection Effectiveness and Design Space-usage Effectiveness.

This indicator scrutinizes how usefully floor space in workstations is used to temporarily stock materials in the form of raw materials, semi-finished products, parts and components. It is suited for analyzing fixed-position layouts as well as product layouts typical of repetitive manufacturing settings, such as assembly lines in the automotive sector. The proposed indicator leverages an appropriate loss structure that features those factors affecting floor space utilization in workstations with regard to supplying and stocking materials.

An Italian manufacturer in the field of electro-technology was used as an industrial case study for the application of the methodology. The application shows how the three indicators work in practice, the effectiveness of OpSE and the methodology as a whole, in diagnosing floor space usage inefficiencies and in properly addressing improvement actions of the internal logistics in industrial settings.

The paper scrutinizes some important Key Performance Indicators (KPIs) dealing with space usage efficiency and identifies some significant drawbacks. Then it suggests a new, inclusive structure of losses and a KPI that not only measures efficiency but also allows to identify viable countermeasures.

The aim of this paper is to examine product formulation screening at the industrial level in terms of multi‐trait improvement by considering several pertinent controlling factors.

The study adopts Taguchi's orthogonal arrays (OAs) for sufficient and economical sampling in a mixture problem. Robustness of testing data is instilled in this method by employing a two‐stage analysis where controlling components are investigated together while the slack variable is tested independently. Multi‐responses collapse to a single master response has been incurred according to the Super Ranking concept. Order statistics are employed to provide statistical significance. The slack variable influence is tested by regression and nonparametric correlation.

Synergy among Taguchi methodology, super ranking and nonparametric testing was seamless to offer practical resolution to product component activeness. The concurrent modulation of two key product traits due to five constituents in the industrial production of muffin‐cake is invoked. The slack variable, rich cream, is strongly active while the influence of added amount of water is barely evident.

The method presented is suitable only for situations where industrial mixtures are investigated. The case study demonstrates prediction capabilities up to quadratic effects for five nominated effects. However, the statistical processor selected here may be adapted to any number of factor settings dictated by the OA sampling plan.

By using a case study from food engineering, the industrial production of a muffin‐cake is examined focusing on a total of five controlling mixture components and two responses. This demonstration emphasizes the dramatic savings in time and effort that are gained by the proposed method due to reduction of experimental effort while gaining on analysis robustness.

This work interconnects Taguchi methodology with powerful nonparametric tests of Kruskal‐Wallis for the difficult problem of non‐linear analysis of mixtures for saturated, unreplicated fractional factorial designs in search of multi‐factor activeness in multi‐response cases employing simple and practical tools.

The search for a more sustainable society depends on more sustainable organisations and, as such, Production (Industrial) Engineering may contribute to this process through the training of professionals with a greater social and environmental consciousness. The purpose of this paper is to present arguments in favour of the integration of Production Engineering and the Millennium Development Goals and evaluate the potential of Production Engineering subareas in contributing to the Millennium Development Goals.

This work is conceptual and integrative in order to provide an original framework. A Brazilian perspective on Production Engineering has been adopted.

A framework is proposed to guide this integration process by providing suggestions for an agenda of opportunities for academics and practitioners in favour of a more sustainable society.

This work presents a new framework integrating Production Engineering and the Millennium Development Goals in order to promote a more sustainable training in Production (Industrial) Engineering field of research.

This paper aims to discuss the challenge for the classical idea of professionalism in understanding the Chinese software engineering industry after giving a close insight into the development of this industry as well as individual engineers with a psycho‐societal perspective.

The study starts with the general review of the sociological concept of profession, professional and specialization of knowledge. Together with revealing the critical challenge from the empirical field of software engineering industry regarding its professionalization, a critique of the neglect of subjective agency in classical conception of professionalism in sociology theory and methodology is set out.

A case study with interpretation of the subject's continuously developing identification with their specialization in knowledge and occupation from their narration of career experience reveals the dynamics in this development process relating to individual, social practice and societal factors.

This paper contributes to empirical research of analyzing the professionalization process of software engineering and software engineers in relation to the concept of professionalism, and it contributes theoretically by discussing the challenge of this process to the development of professionalism within this highly knowledge‐based industry in a Chinese societal context.

The industry is relying on the preventive maintenance techniques that can minimize failures and provide industrial plants with effective equipment, but in many companies the maintenance tasks are performed very frequently and not as per plan and do not take into consideration the conditions of the plant and equipments. The failure of each and every component needs to be studied in order to choose the best maintenance strategy. This paper presents a fuzzy VIKOR (Multicriteria Optimization and Compromise Solution) technique which is used in developing a comprehensive approach for maintenance strategy selection in the Deinking plant of the paper industry to choose the appropriate maintenance strategy thereby reducing the unnecessary cost incurred on the maintenance.

In this paper, the Fuzzy VIKOR based methodology was applied for determining the maintenance criticality index of the deinking plant of the paper industry. The effect of failure of components were evaluated by three maintenance experts on five performance criteria that is chance of failure, chance of non-detection, downtime length, severity, spare part criticality. The components were ranked according to the maintenance criticality index and thereby implementing the appropriate maintenance strategy.

The Fuzzy VIKOR technique was applied to calculate the ranking of various components of paper industry based on the views and judgment of three maintenance experts. The proposed technique suggested the appropriate maintenance strategy for various components taking into consideration the maintenance criticality index of the components.

The proposed technique will help the maintenance managers to solve a discrete problem with non-commensurable and conflicting criteria. The study will help the industries to reduce the unnecessary maintenance tasks and thereby reduce the maintenance cost. This will help the maintenance practitioners in choosing the best and most effective strategy for the organization with regard to the market and company situation especially in the changing business requirement of Industry 4.0.

The purpose of this paper is to investigate the relations in the Marketing/Operations interface through the analysis of data of the operational reality of a Brazilian company with a low technological intensity. The study aims to quantify and determine the impacts of marketing decisions on delivery performance and on flexibility of the operations area.

A longitudinal case study was conducted and the variables used in the model were derived from established theories and were evaluated with artificial neural networks. The case of a food manufacturing company was selected to reflect the relations in the marketing/operations interface of a low technological intensity enterprise.

The results show that the decisions on Place/Channel, Price and Product dimensions of marketing exert a significant impact on flexibility and delivery performance of the operation area.

The findings of the case study cannot be generalised and the outcomes are specific to just one firm. However, the approach lends itself to replication, particularly within low technological intensity companies.

Prior studies have focussed on coordination among functional areas as marketing and operations at higher levels of abstraction. The study contemplate empirical propositions through the data analysis of a company with a low technological intensity that can be used to improve managers' decisions and alignment in the Marketing/Operation Interface.

Facility layout is a classical industrial/production engineering problem. Good layout will help any company to improve its business performance. Presents a general overview of the facility layout problem and includes information about approaches to the solution of the problem. Discusses the role of the computer; and the contribution of facility layout to an organization’s competitive advantage. Describes experiences of organizations with facility layout.