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Article
Publication date: 6 November 2017

Ali M. Abdulshahed, Ibrahim A. Badi and Mohamed Mehemed Blaow

The purpose of this paper is to propose a supplier selection method using grey system theory for a steelmaking company in Libya.

Abstract

Purpose

The purpose of this paper is to propose a supplier selection method using grey system theory for a steelmaking company in Libya.

Design/methodology/approach

In order to tackle incompleteness and imprecision of human’s judgments, grey numbers were used. This work uses a grey-based approach to represent decision makers’ comparison judgments and extent analysis method to select the best supplier. Therefore, an example of a selection problem of a steelmaking company in Libya was used to illustrate the proposed approach.

Findings

Supplier selection in a supply chain is a critical strategic decision for company’s success and has attracted much attention of both academic scholars and decision makers. The authors have found that the Grey model can play an important role in improving supplier selection strategy, especially when it is in a situation where complex sustainability environments (i.e. Libya) exist.

Originality/value

No literature has been found till date for selection of supplier using grey system theory in a steelmaking company in Libya. An attempt in this regard could enhance a decision-making technique for selecting the best suppliers for the selected case company.

Details

Grey Systems: Theory and Application, vol. 7 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Book part
Publication date: 13 September 2018

Samane Maroufi, Claudia A. Echeverria, Farshid Pahlevani and Veena Sahajwalla

Every year, tens of millions of the 1.4 billion cars on the world’s roads are decommissioned. While the ferrous and other metals that constitute about 75% of a vehicle by…

Abstract

Every year, tens of millions of the 1.4 billion cars on the world’s roads are decommissioned. While the ferrous and other metals that constitute about 75% of a vehicle by weight can be readily and profitably recycled, the remaining mix of plastics, glass, composites, complex materials, fragments and contaminants are mainly destined for landfill as automotive shredder residue (ASR). For every car, approximately 100–200 kg of ASR is disposed of in landfill, posing a growing technical and environmental challenge worldwide. The recovery of the ASR for high-end application is the focus of this study, aiming to optimise the use of these valuable resources and minimise the extractive pressure for raw materials, a future green manufacturing, contributing towards a zero waste circular economy. As the dissolution of carbon into iron is a key step in the manufacture of iron-carbon alloys, the feasibility of utilizing the waste polymers within ASR as sources of carbon in different areas of pyrometallurgical processing was investigated. Polypropylene and rubber, in a blend with metallurgical coke, were used as carbonaceous substrates and the slag-foaming phenomenon was investigated via the sessile drop technique in an argon environment at 1,550°C. The results indicated the rubber/coke blend achieved significantly better foaming behaviour, and the PP/coke blend exhibited a moderate improvement in slag foaming, in comparison to 100% metallurgical coke. The overall results indicated the incorporation of ASR had significant improvement in foaminess behaviour, increasing furnace efficiency.

Details

Unmaking Waste in Production and Consumption: Towards the Circular Economy
Type: Book
ISBN: 978-1-78714-620-4

Keywords

Expert briefing
Publication date: 30 May 2022

The compound is key to nickel-manganese cobalt (NMC) batteries, gaining market share for use in electric vehicles (EVs). Manganese amounts to only 2% of EV cathode…

Details

DOI: 10.1108/OXAN-DB270536

ISSN: 2633-304X

Keywords

Geographic
Topical
Content available
Article
Publication date: 1 October 1998

173

Abstract

Details

Aircraft Engineering and Aerospace Technology, vol. 70 no. 5
Type: Research Article
ISSN: 0002-2667

Keywords

Article
Publication date: 1 November 1978

SAID Sir Harold Wilson when he was Prime Minister, “One man's wage increase is another worker on the dole.” It seems as if that axiom has been forgotten. Members of this…

Abstract

SAID Sir Harold Wilson when he was Prime Minister, “One man's wage increase is another worker on the dole.” It seems as if that axiom has been forgotten. Members of this Labour Government which, it must be admitted, has striven manfully and successfully to bring inflation down, are now speaking with hopeless fatalism of any army of workless likely to reach over three million in a heartbreaking short space of time.

Details

Work Study, vol. 27 no. 11
Type: Research Article
ISSN: 0043-8022

Book part
Publication date: 24 November 2017

Timur Atnashev and Teimuraz Vashakmadze

To analyze internationalization patterns among large Russian multinational corporations (MNCs).

Abstract

Purpose

To analyze internationalization patterns among large Russian multinational corporations (MNCs).

Approach

Case study analysis of systematic internationalization attempts within three industries: IT, banking, and steel. For case studies, secondary data was used along with industry expert interviews.

Findings

The first finding is that Russian firms actively pursuing internationalization strategies through mergers and acquisitions (M&As) and greenfield investments were not as successful as several optimistic assessments had earlier suggested. Few global corporate champions emerged among Russian MNCs, despite a decade of record high outward foreign direct investments (OFDI). Secondly, we observed the unique trend of splitting operations between international and Russian businesses, which proved more sustainable than operating as a single firm. For example, the IBS-Luxoft group achieved success through gradual legal and organizational separation of branches in order to serve rising demand in developed markets and from its Russian business within the same industry. This double-headed strategy divides a business into two parts that are controlled by the same owners, but operate independently: one firm operates within the home market, while another firm aims to expand globally. This seems to be a typical trend, confirming recent findings for Russian small and medium enterprise (SME) internationalization and reinforcing earlier literature on institutional constraints in the Russian economy.

Research limitations

We analyzed major cases from three actively internationalizing industries. For each industry, we extensively analyzed one main case in particular. Industries’ choice also affects specific internationalization strategies.

Originality

This study identifies two distinct approaches in the literature on Russian business internationalization and attempts to combine both. We will also highlight organizational dilemmas as well as patterns in Russian businesses’ successful and failed internationalization strategies over the last decade. We identified an original double-headed internationalization strategy consisting of the separation of the national and global businesses, rather than leveraging their synergy. We will also question the established optimistic assessment of Russian MNC internationalization.

Expert briefing
Publication date: 6 January 2021

The steelmaking ingredient was barely affected by the pandemic in March-April 2020 and gained 72% over the year. The main suppliers stepped up production and China-bound…

Details

DOI: 10.1108/OXAN-DB258589

ISSN: 2633-304X

Keywords

Geographic
Topical
Article
Publication date: 5 October 2015

Theofani Tzevelekou, Spyros Papaefthymiou, Vasiliki Panteleakou, Athanasios Vazdirvanidis, Dimitris C. Papamantellos and Panagiotis Sismanis

A failed disc that was forged from S355J2 round bar was investigated in order to determine the failure route cause. The purpose of this paper is to determine the defects…

Abstract

Purpose

A failed disc that was forged from S355J2 round bar was investigated in order to determine the failure route cause. The purpose of this paper is to determine the defects and route cause analysis regarding their origin.

Design/methodology/approach

Macroscopic evaluation, microstructure observation using light optical metallography and scanning electron microscopy with EDX analysis were the techniques used to analyse and characterize the defected areas.

Findings

Macro-inclusions (up to 850 µm) that correspond to high melting aluminium rich calcium-aluminate particles were detected. Their formation, possibly due to improper calcium treatment during ladle furnace steel refining process might be associated with clogging problems at casting. SEM-EDX analysis revealed whitish spots containing Zr that could be related to submerged entry nozzle (SEN) erosion/breakage. Characteristic is the large size and unusual shape of the traced particles, as well as the presence of low Si, Na, K. The findings indicated that nozzle clogging and/or breakage at casting was most possibly the root cause of the product’s quality degradation.

Originality/value

After extended root cause analysis, specific countermeasures are proposed to avoid clogging phenomena. The suggestions are based on the findings taking into account restrains of the steel-making process. Emphasis was laid in detecting the weaknesses that lead to product quality degradation and consequently in optimizing the steel-making process. Such incidents are often found during steelmaking a useful suggestion to steelmakers is to mark and remove cast parts after SEN problems are encountered. In this way quality issues in intermediate and/or final products will be avoided.

Details

International Journal of Structural Integrity, vol. 6 no. 5
Type: Research Article
ISSN: 1757-9864

Keywords

Article
Publication date: 26 April 2022

Saroj Kumar Singh, Alok Raj, J. Ajith Kumar and Cyril Foropon

The purpose of this paper is to identify potential constraints and determine the constraint structure in a steel manufacturing plant. “Potential constraint” is defined as…

Abstract

Purpose

The purpose of this paper is to identify potential constraints and determine the constraint structure in a steel manufacturing plant. “Potential constraint” is defined as a factor that is either a constraint at present or can become one in the future and “constraint structure” is used to denote the network of influences between the potential constraints in an organization.

Design/methodology/approach

A three-step methodology was followed. First, potential constraints in a steel manufacturing plant were identified with a literature review and expert inputs. Then, the fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique was applied to uncover the structure and finally, an ex-post validation and refinement of the results was done with help from other experts.

Findings

A total of 10 key potential constraints to steel manufacturing were identified. The two outputs of fuzzy DEMATEL – the influence scatter plot (ISP) and the influence network diagram (IND) – together reveal the constraint structure. The 10 potential constraints could be classified into three types – influencers, mediators and influenced – respectively. Of these “Top management commitment (TMC)” and “Clear vision and long-term planning (CLP)” influence other factors the most, and are themselves influenced the least; while “Customer Relationship Management (CRM)” is most influenced by other factors, while influencing other factors the least.

Practical implications

Potential constraints and the constraint structure can help decision makers in a steel manufacturing plant to identify which organizational factors to address and achieving the plant's goals.

Originality/value

This is the first study that analyzed organizational level constraints in a steel manufacturing context.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 31 January 2022

Simone Massulini Acosta and Angelo Marcio Oliveira Sant'Anna

Process monitoring is a way to manage the quality characteristics of products in manufacturing processes. Several process monitoring based on machine learning algorithms…

Abstract

Purpose

Process monitoring is a way to manage the quality characteristics of products in manufacturing processes. Several process monitoring based on machine learning algorithms have been proposed in the literature and have gained the attention of many researchers. In this paper, the authors developed machine learning-based control charts for monitoring fraction non-conforming products in smart manufacturing. This study proposed a relevance vector machine using Bayesian sparse kernel optimized by differential evolution algorithm for efficient monitoring in manufacturing.

Design/methodology/approach

A new approach was carried out about data analysis, modelling and monitoring in the manufacturing industry. This study developed a relevance vector machine using Bayesian sparse kernel technique to improve the support vector machine used to both regression and classification problems. The authors compared the performance of proposed relevance vector machine with other machine learning algorithms, such as support vector machine, artificial neural network and beta regression model. The proposed approach was evaluated by different shift scenarios of average run length using Monte Carlo simulation.

Findings

The authors analyse a real case study in a manufacturing company, based on best machine learning algorithms. The results indicate that proposed relevance vector machine-based process monitoring are excellent quality tools for monitoring defective products in manufacturing process. A comparative analysis with four machine learning models is used to evaluate the performance of the proposed approach. The relevance vector machine has slightly better performance than support vector machine, artificial neural network and beta models.

Originality/value

This research is different from the others by providing approaches for monitoring defective products. Machine learning-based control charts are used to monitor product failures in smart manufacturing process. Besides, the key contribution of this study is to develop different models for fault detection and to identify any change point in the manufacturing process. Moreover, the authors’ research indicates that machine learning models are adequate tools for the modelling and monitoring of the fraction non-conforming product in the industrial process.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

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