The organisations having a futuristic look and aiming to impose their presence in the industrial field for a long possible term, are seeking for finding solutions linked to controlling their cash flow and assessing their competitiveness performances. Therefore, the purpose of this paper is to propose a new quality and cost value stream mapping for monitoring the costs consumption and assessing the competitiveness of a company. We use three key concepts namely life cycle costing for estimation of the most influential costs on the manufacturing process, the weighted DPMO and Sigma level for assessing the quality level and the competitiveness of the company. Finally, the data obtained are mapped using value stream mapping method for enabling the determination of dysfunctions in the cost and quality context.

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Electronic waste (e-waste) is one of the fastest growing waste streams in the world. Notwithstanding increasing concern worldwide, e-waste has not yet been discussed in depth in the Middle East and North Africa (MENA) region. This study first reviews the literature regarding the estimation of e-waste in the MENA region. It then gives an estimate of the past and future trends in the generation of obsolete computers in Algeria. For this purpose, the study combines two models: the Carnegie Mellon model and the market supply (distribution delay) model. The Carnegie Mellon model offers the following options for obsolete computers and monitors: the device could be reused, stored, or discarded. The amounts of devices falling into each category were determined based on these options. The outcomes from the market supply (distribution delay) model show that high amounts of computer and monitor waste were registered for the period from 2014 to 2016.

Waste electrical and electronic equipment (WEEE) generated in emerging countries is increasing. This study presents a methodology to improve assessment and monitoring WEEE in Algeria. The proposed methodology is a two-step approach. The first step is the collection and collation of existing data from different national and international sources. In the second step, different assessment and forecasting methods are applied. Forecasting methods were selected from those models which provided minimum error indices. The paper considers also the availability and reliability of data in order to provide a future reliable assessment of WEEE in Algeria. The study revealed that the forecasting methods do not have a big influence on the results contrary to the inputs of the model.

Every modern company should measure the value of its intellectual capital and to report to complement the traditional annual balance sheets. The purpose of this work is to measure the intellectual capital in an Algerian company (or production system) using the Weightless Wealth Tool Kit (WWTK). The results of the measurement of intellectual capital are supplemented by traditional financial ratios. The measurement was applied to the National Company of Wells Services (ENSP) in Hassi Messaoud city, in the south of Algeria. We calculated the intellectual capital (intangible resources) of the ENSP to help the organization to better capitalize on its potential of workers and their know-how. The intangible value of the ENSP is evaluated at 16,936,173,345 DA in 2015.

With the increasing growth of the chemical and process industries, it is necessary to ensure the safe operation of their complex and often hazardous installations, given their proximity to residential areas. Several techniques, such as fault tree analysis (FTA), bow-tie analysis (BTA), and Bayesian belief networks (BBNs), have been developed for adequate probabilistic risk assessment and management. The current work is aimed at performing a brief statistical review of the use of Bayesian networks in the chemical and process industry within the last decade. The review reveals that Bayesian networks have been used extensively in various forms of safety and risk assessment. This trend is attributable to the complexity of the installations found in this industry and the ability of BBN to intuitively represent these complexities, handle uncertainties, and update event probabilities. The paper is concluded with an illustrative example of the use of BBN to investigate the effectiveness of the safety barriers of a gas facility.

Fault diagnosis is the best discipline to control the operation and maintenance costs of the wind turbine system. However, the fault diagnosis of wind turbine finds difficulties with the variation of wind speed and electrical energy (generator torque). In this work, the proposed fault diagnosis approach is based on the Feature set algorithm, manifold learning and the Support Vector Machine classifier. First, the construction of the feature set is very important step, with the high dimension after application the MAED (Manifold Adaptive Experimental Design) algorithm on the data set. Moreover, the NPE (Neighborhood Preserving Embedding) manifold learning algorithm is applied for directional reduction of feature set by the eigenvectors; it is easy to use as the input for the last step. Finally, the low dimensions of eigenvectors are exploited by the (SVM) Support Vector Machine classifier for recognition fault and making the maintenance decision. This approach is implanted on the faults of the benchmark wind turbine and gives the best performance.

In this paper, we present the application of knowledge engineering and externalisation of tacit knowledge in manufacturing industry, in order to improve the performance of a production system and save the knowledge capital of the company. The main aim of this study is to propose a knowledge model for manufacturing task combining common knowledge acquisition and design support (CommonKADS) and methodology for acquisition of tacit knowledge (MACTAK) methodologies, using two different knowledge base modelling based on two categories: (i) ontology and (ii) expert knowledge base. In that purpose, we suggest a process dedicated to industrial manufacturing, allowing to capitalise knowledge by: (1) Externalisation of tacit knowledge by MACTAK-methodology in industrial processes, (2) using knowledge engineering method; CommonKADS methodology, (3) Formalizing and modelling the domain knowledge using ontology and inference model, (4) presenting the implementation tool to support the knowledge model and (5) reusing the manufacturing knowledge model in decision support systems. The three pillars of methodology are: the externalisation process, Knowledge representation technique and quality tools. The proposed model is applied in manufacturing monitoring systems.

The present study deals with the performance of a 1.6kWp grid connected PV system installed at Batna University, in Algeria. The average solar energy received was 5.21 kWh/m².d, the grid connected PV system seems to be a good candidate for generating electricity in this region. The system was monitored during one year of continuous operation and data analysis to evaluate the performance of the grid connected PV system. The performance ratio of the system ranged between 51 and 61%. Furthermore, the total produced energy by the PV array was 1931.7kWh and the supplied energy to the grid was 1705kWh. The annual final yield was 1065.6kWh/kWp. Moreover, an analysis of the energy losses in the system was performed, this makes it possible to determine the effect of the capture and system losses on the total energy balance of the system. All the electricity generated by the system was fed into the internal electrical grid of the university.

Several applications in the agro food sub-sector have been classified as suitable to be supplied by solar heating systems. The present work deals with the potential evaluation of solar thermal energy under climatic conditions of Algeria. In a first part, an experimental investigation conducted on small scale solar water heating system is presented followed by simulation. The experimental tests revealed the thermal behavior of the system as well as the outlet temperature levels which can be reached by locally manufactured flat plat collectors. The second part presents the potential of solar heat for industrial applications, particularly those consisting of heating make-up water and water feedback from heat recovery wich exists in almost all the agro food industries. Thus, water inlet temperature through the secondary circuit is considered to be ranging from 20 to 90°C. The results showed that the annual specific energy yield delivered by the solar system decreases by increasing water feedback temperature. 

In recent years, companies have emerged in an advanced competitive environment. To meet the requirements of cost reduction, customer demand, minimising delays, quality and variety improvement, companies must improve their performance to remain competitive, survive and expand. To achieve this goal, several models are used such as total quality management, Kaizen, just in time, enterprise resource planning, business process reengineering and Six Sigma, etc. In this work, we look for an effective model (drawn from Six Sigma approach) used mainly to warrant the competitiveness of a company denoted as the weighted defects per million opportunities model. The aim of this paper is to apply this model to measure process levels (weights) and assess the company competitiveness. The results of this model are applied in a real manufacturing system which produces gas bottles.

The industrial sector accounts for almost one fourth of the final energy consumption in Algeria. An energy survey was carried out in three Algerian dairies, and the energy use and cost analysis is presented in this article. Electricity and natural gas are the main resources that are used in the dairy industry. The specific energy consumption related to electricity and natural gas was found to be in the ranges of 0.03–0.08 kWh/kg and 0.10-0.22 kWh/kg respectively. Also, a relationship of energy consumption, energy costs and production is presented and the findings could be used to establish an energy management system aimed at using energy more efficiently. Finally, this paper calls for more investigations of other industries to obtain reliable indicators.

The purpose of this paper is to compare between three methods of intellectual capital (IC) measurement; intellectual capital dynamic valuation (IC-dVal), value added intellectual coefficient (VAIC), and national intellectual capital index (NICI). The three methods are the most used in practice; we used 24 criteria covering important aspects of IC to do general comparison. According to ten criteria, we compared and prioritised them using analytic hierarchy process (AHP). The results of this comparison show that the methods are close for some criteria and distant for other criteria. The prioritisation with AHP found that NICI method is the most method responding to the criteria, namely: macro measure, guidelines of the method, dynamic valuation, involved levels of business, usability by stakeholders, covered aspects of IC, quantifiability, frequency of use and applicability. IC-dVal is the second one and VAIC is the third method responding to the criteria. The analysis could give more significant results using larger set of criteria. This is the first research prioritising methods of measurement of IC using AHP analysis

The purpose of this paper is to propose a hybrid method SKACICM of development of knowledge management systems. Based on weaknesses of the method of performance dashboards SKANDIA, we proposed a pragmatisation and adaptation of Skandia to give (ASKANDIA), by enrichment of its performance book. We ameliorated CICM model against the requirements of GERAM to give ACICM model by mappings between their proposed metamodels. We tried to hybridise ACICM, ASKANDIA and business intelligence to propose a new method SKACICM of development of knowledge management systems. We applied SKACICM on a cement company to develop software containing three main modules, module knowledge management, module business intelligence and performance dashboard system. The developed system ameliorated the performance of the enterprise by 26% and could be generalised to other manufacturing or service systems.

In this study, a metaheuristic based on the Non-dominated Sorting Genetic Algorithm type II (NSGA-II) is proposed to solve the Multi-Criterions Job Shop Scheduling Problem (MCJSSP) under resources availability constraints. Availability periods and starting time of maintenance activities are supposed to be flexible. The MCJSSP requires, simultaneous minimization several antagonistic criteria, such as the maximum completion time of all jobs (Makespan), production cost and maintenance cost. To validate the proposed approach we tested it on forty-four instances references. The results show that our approach is experimentally promising to solve practical problems.