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Making decisions on production and maintenance separately, as is often done in practice and research literature, may not result in overall optimization. This paper aims to propose a joint method that better integrates production planning and maintenance at the tactical level. The potential of improving the performance of the classic planning method is also explored.

An integrated production planning and maintenance model is proposed. The production capacity losses resulted from both preventive and corrective maintenance activities are considered. Meanwhile, the reliability deterioration of the machine is considered to be operation dependent. An iterative approach is presented to find a solution for the nonlinear model through iteratively solving a sequence of mixed integer linear programming instances, accompanied by modification of some parameters prior to each iteration. Computational experiments are conducted to evaluate the performance of the proposed method compared with three other methods, including two methods based on separate planning and one integrated model.

The superiority of the proposed method compared with all the other three methods is demonstrated. Thus, the values of both integrated planning and considering operation-dependent failures are testified. The advantage of the proposed method is highlighted in the cases of high capacity utilization, long maintenance durations and low maintenance costs. The performance of the two methods based on separate planning is sensitive to the system utilization, and when utilization is high, the one with an availability-sensitive objective function defined for the maintenance problem performs better.

Few studies have been carried out to integrate decisions on production lot and maintenance. Their considerations are either incomplete or not realistic enough. A more comprehensive and realistic integrated model is proposed in this paper, along with an iterative solution algorithm for it. A potential way to improve the performance of the classic planning method with its simplicity preserved is also presented.

This paper aims to evaluate the consumer acceptance of Bordô and Isabel wines from innovative winemaking in order to increase red wine consumption by consumers to obtain nutritional benefits.

All wines were produced by a standard procedure of vinification. Pre‐drying treatment aimed at drying the grapes up to 22°Brix and static pomace wines presented the constant contact between the must and pomace. Sensory acceptance was carried out by 80 consumers who evaluated eight samples (six experimental wines and two commercial wines) concerning the attributes: appearance, aroma, body, flavor and overall acceptance.

Experimental wines presented higher acceptance when compared to commercial wines and cluster analysis shows the splitting of consumer preferences, highlighting the higher acceptance of traditional Bordô wine and static pomace samples in all sensory attributes. Pre‐drying process enhances the concentration of coloured compounds, to highlight the appearance acceptance of these samples.

Although this paper has limited the consumer acceptance of red table wines, the innovative treatments will be applied in Vitis vinifera red wines.

The wide acceptance of static pomace and pre‐drying wines has promoted further information about innovative winemaking that can be applied in Brazilian and worldwide wineries.

The innovative treatments can change sensorial features of wines and therefore influence the choice of consumers as well as enhancing the nutritional benefits of red wines.

The pre‐drying and static pomace winemaking are the novelty of this study and the wide acceptance of the sensory attributes concerning these treatments indicates the potential for application in wineries.

Planning of manufacturing and maintenance activities together, creating a balance between maintenance and production parameters and developments on maintenance will prevent technical and economic losses and increase production efficiency. Optimizing production and maintenance scheduling enable us to see how maintenance parameters (β, η, t_p, t_r, a_[o]) will affect production performance, completion time (Ec.) and maximum machine availability, and shows which maintenance parameters minimum completion time (Ec_min) will be provided. Difference between Ec_min and maximum completion time (Ec_mak) effect to the production costs will be calculated. The purpose of this paper is to show how a genetic algorithm (GA) procedure is successfully applied to the integrated optimization model to determine optimum production policies based maintenance parameters.

GA is used for optimization and a computer program is prepared to make optimization for integrated preventive maintenance and production planning (IPMPP). Using the program, experimental studies are carried out with different number of jobs be done, to optimize production policy taking maintenance parameters into account.

Numerous experiments have been conducted with developed GA computer program and see maintenance parameters (β, η, t_p, t_r, a_[o]) effect to the production performance, Ec and maximum machine availability and at which maintenance parameters Ec_min will be provided, and also operating cost saving and maintenance parameters how affect Ec subjects are examined. Due to optimal preventive maintenance (PM) and production sequence arrangement and application of PM provided by GA, Ec_min is greatly decreased.

In this paper, GA procedure is successfully applied to the integrated optimization model to determine optimum production policies based maintenance parameters.

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.

The purpose of this paper is to develop an efficient tool to ensure traceability data entry based on RFID and improve the detection of fakes inside the supply chain.

First, the authors put forward a secure traceability system with a cryptographic operator that improves efficiency, saves costs and is adaptable to all types of supply chains. Second, the authors implement the system in a food manufacturing company, show the compatibility of the system with the initial production chain and demonstrate its improvement.

The authors have economically and technologically improved the detection of faked goods in the supply chain by means of a cheap and scalable system based on RFID.

The system has been tested in a manufacturing point of the supply chain, not in the supply chain as a whole. As traceability is additive in character, the results can be generalized and applied to each part of the supply chain.

A prototype has been built and implemented for a food manufacturing company. It meets all the specifications required for detection of fakes in manufactured products.

Unlike other existing products used to detect fakes through traceability, this system identifies fakes and potential counterfeits, significantly reducing the cost of security management. Another important difference is that verification can be performed by a third party not involved in the system, without loss of security.

In many manufacturing systems, machines are subject to preventive maintenance. This paper aims to schedule the operations of jobs and preventive maintenance tasks in such a way that the completion time of jobs and preventive maintenance tasks is minimized.

An heuristic approach based on artificial immune algorithm is proposed for solving the multiple‐route job shop‐scheduling problem subject to fixed periodic and age‐dependent preventive maintenance tasks. Under fixed periodic assumption, the time between two consecutive preventive maintenance tasks is assumed constant. Under age‐dependent assumption, a preventive maintenance task is triggered if the machine operates for a certain amount of time. The goal is to schedule the jobs and preventive maintenance task subject to makespan minimization.

In addition to presenting mathematical formulation for the multiple‐route job shop‐scheduling problem, this paper proposes a novel approach by which one can tackle the complexity that is raised in scheduling and sequencing the jobs and the preventive maintenance simultaneously and obtain the required schedule in reasonable time.

Integrating preventive maintenance tasks into the scheduling procedure is vital in many manufacturing systems. Using the proposed approach, one can obtain a schedule that defines the production route through which each part is processed, the time each operation must be started, and when preventive maintenance must be carried out on each machine. This, in turn, results in overall manufacturing cost reduction.

Using the approach proposed in this paper, good solutions, if not optimal, can be obtained for scheduling jobs and preventive maintenance task in one of the most complicated job shop configurations, namely, multiple‐route job shop. Thus, the approach can dominate all other simpler configurations.

This chapter investigates the trends in international and European legal and policy regulation of the process related to carbon capture and storage (CCS). The global endeavor that seeks to limit carbon dioxide emissions has come to recognize CCS as an indispensable ally. This chapter offers an up-to-date and comprehensive commentary to the relatively new and developing area of international regulation of the process of CCS, a dimension that might yield significant effects on the environment and, overall, sustainable development. It reveals a constantly growing trend of an enhanced awareness about the indispensable role and effects of the CCS on wider climate aspirations and, to that effect, also a need for a stable and effective international regulatory framework. The key barriers that are preventing the wider implementation of CCS projects, however, relate primarily to two extra-regulatory processes, which is the policy uncertainty at national levels and financial shortcomings. This background presents a window of opportunity for entrepreneurship and policy invention.

Production-related industrial zones, super structures and infrastructures are constructed by the construction industry. Nearly all industries and their environmental emissions are influenced by the construction industry including its sub-industries, companies and their supply chains. Furthermore, cities play an important role in economic growth. Cities are hubs for productivity, production, supply and demand, and innovation with the help of their human capital and built environment (e.g. offices, factories, industrial zones, infrastructures, etc.).

Industrial growth fosters urbanisation which is vital for the supply side in the economy to reach to the human resources. Urbanisation which supports industrial growth obstacles industries’ efficiency due to urbanisation problems (e.g. traffic, air and water pollution, health problems).

Construction industry and its sub-industries affect total factor productivity growth in nearly all industries. Construction industry can be a facilitator industry for economic growth and industrial growth considering total factor productivity growth and environment aspects. All industries’ green and sustainable total factor productivity growth can be supported by rethinking construction industry, its sub-industries and their outputs (e.g. construction materials, built environment, cities) as well as construction project management processes.

This chapter aims to introduce carbon capturing smart construction industry model to foster green and sustainable total factor productivity growth of industries. This chapter emphasises current and potential roles of construction industry, its sub-industries and their outputs in fostering other industries’ growth through green and sustainable total factor productivity growth. It focusses on carbon capturing technologies and design at different levels. Furthermore, this chapter emphasises cities’ role in green and sustainable total factor productivity growth. This chapter provides recommendations for construction industry policies and carbon capturing cities/built environment model to solve urbanisation problems and to foster industrial growth and green and sustainable total factor productivity growth. This chapter is expected to be useful to all stakeholders of the construction industry, policy makers, and researchers in the relevant field.

Seeks to focus on operations priority patterns and operations strategy. Configurations by testing them in a specific environment which contributes to demonstrating their applicability and generalizability.

Using data from 130 Spanish companies with project process organization, their operations strategy is analyzed as a whole, without the following of a trade‐off pattern being observed.

Cost, conformer and innovation strategy types, compared with other operations strategy configurations regarding variables used to develop project management configurations, for the most part exhibit a coherent behaviour, giving support to operations strategy validation at a higher theoretical level.

The two most important limitations are the relatively small sample size used in the study and the results obtained with the organization structure variable. Similar studies in other specific production process contexts should also be undertaken.

Results obtained contribute to demonstrating the applicability of the operations strategy framework to the study of operations management in different environments and its coherence with the specific variables that are used to characterize them.

This study is virtually breaking new ground, prompted by recent calls for empirical research and for testing developed theories on operations management.

However, due to the huge number of studies and on the other hand to be new and creative, the represented models and methods – as the two main parts of this field – have been got more complicated, which consequently have been turned into unpractical research studies for the realistic situations. Therefore, the purpose of this study is the representation of a novel and simple method to deal with the aforementioned gap.

To this end, Fazl-Tash method have been proposed, in which a thorough and complete model including 114 criteria and a simple technique to rank and select the best supplier have been presented. Sustainability and resiliency are considered in collecting criteria effective on supplier selection.

The method was carried out in a case study in an industrial company. The efficiency of the proposed method is evaluated in comparison with other conventional approaches.

As selecting the supplier plays a crucial role to bring some important advantages for companies, such as coping with the cost and time problems and influencing the majority of contemporary markets’ requirements, in recent years, there have been representing more effective studies in the supplier selection literature.