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PurposeThe current research aims to analyze the literature to determine its strengths and weaknesses and extract the required information, which will be used to identify the characteristics of the highly competitive organization (HCO), define it and identify the HCO's critical success factors (CSFs). Finally, the future research agenda will be proposed.Design/methodology/approachA multiple stages research methodology was used to fulfill the research objectives. The research started with the systematic literature review (SLR). Then, focus group discussions and Pareto analysis were used to fulfill research objectives.FindingsEleven points were identified in the research to represent the characteristics of the HCO. Then, the HCO was defined based on the elements of these points. Moreover, the vital few CSFs to successfully implement many research scopes were identified. Then, the CSFs of the HCO was generated based on these vital few CSFs.Research limitations/implicationsThe main limitation of the current research is the literature sample size. A larger sample selection could enrich the generated lists with many other CSFs.Practical implicationsMany implications points were highlighted in this research which showed the importance of the current research for academic and practical audiences.Originality/valueThe SLR process showed that the reviewed literature lacked a consolidated list of the HCO characteristics and a clear definition of the HCO. Moreover, the reviewed literature lacked a unified list of the HCO CSFs. Therefore, the current research approach is novel and original.

The purpose of this research is to conduct a Systematic Literature Review to identify organizational excellence methodologies (OEMs) from the state of the art literature, classify them based on their business sector, generate a unified list of organizational excellence (OE) critical success factors (CSFs), and propose future research agenda. A comprehensive analysis conducted on publications/year, publications/journals, journals’ rank, research methods, business sector, publications’ research area, and much more. The analysis reveals the identification of 46 OEMs, a unified list of 47 OE CSFs, and proposing future research agenda that include testing OEMs in the same business sector but in different countries, regions, or even different business sectors; conducting longitudinal studies on OEMs research scope; developing OEMs for the public sector and NPOs; studying the OE aspects in the MENA region; the researchers from the MENA, Africa, Malaysia, China, and the USA should put more effort to contribute to the OE scope; exploring the OE CSFs, barriers, and challenges on the different levels, business sectors, and geographical locations; testing the importance of the unified list of CSFs for organizational performance; developing a methodology to facilitate OEMs adaptation process; integrating some of the OEMs that never integrated before and test their impact on organizations’ performance; integrating the sustainability concept with the BEMs or OE concept; studying the OE applications in the new era of digitization, globalization, the Internet of Things, and industry 4.0; and proposing a methodology or framework to maintain an excellent performance level beyond the implementation stage.

Wire electrical discharge machining (WEDM) process used in a wide spectrum of industrial applications. AISI 1045 is medium carbon steel, because of its excellent physical and chemical properties, it is used in many applications. However, the review of the state of the art literature reveals that literature is lacking research to optimize WEDM process for machining AISI 1045 steel. The objectives of this research are building ANN model to predict metal removal rate (MRR) and surface roughness (Ra) values for machining AISI 1045 steel, identifying the significance of the pulse on-time (TON), pulse off time (TOFF) and servo feed (SF) for the MRR and Ra, and selecting optimal machining parameters that give maximum MRR value and that give the minimum Ra value. Taguchi method (Design of Experiments), artificial neural network (ANN), and analysis of variances (ANOVA) used in this research as a methodology to fulfill research objectives. This research reveals that the architecture (3-5-1) of ANN models is the best architecture to predict the Ra and MRR with about 98.136% and 97.3% accuracy respectively. It can be realized that TON is the most significant cutting parameter affecting Ra by P % value 42.922% followed by TOFF with a P % value of 24.860%. SF was not a significant parameter for Ra because of Fα > F. For MRR, the most significant parameter is TON with a P % value of (71.733%), i.e. about three times the TOFF P % value (21.796%) and the SF parameter has a small influence with P % value 3.02%. The analysis confirmed that the optimal cutting parameters for maximum MRR were: TON at the third level (25 µs), TOFF at the first level (20 µs), and SF at the third level (700 mm/min). On the other hand, the optimal cutting parameters for minimum Ra were: TON at the first level (10 µs), TOFF at the third level (40 µs), and SF at the first level (500 mm/min). Future work may focus on optimizing the WEDM process for machining other types of materials or other sets of parameters and performance measures.

Electrical discharge machining (EDM) is one of the non-traditional machining processes characterized by its ability to machine parts that electrically conductive but difficult to be machined in the traditional machining processes due to its high hardness, complex geometry, and low tolerances. To minimize EDM process cost, ensure the highest process efficiency and achieve the highest product quality, the EDM process needs to be optimized. The aim of this research is optimizing EDM process parameters for machining HSS (AISI M2) material by use of copper electrode and brass electrode considering conflicting performance measures in one and multidimensional levels. The performance measures used in the current research are material removal rate (MRR) and electrode wear rate (EWR), while machining parameters that will subject to optimization process are current (A), pulse on (TON), and pulse off (TOFF). During optimization stages, the Taguchi method, signal to noise ratio (S/N ratio), and analysis of variances (ANOVA) will be used in the first stage to find the optimal machining parameters for each performance measure and for each electrode material. In the second stage, multidimensional optimization approach encompasses using the calculated S/N ratio as input from the first stage, fuzzy logic and ANOVA to calculate multi response performance index which will be used to select optimal machining parameters for each electrode and then select the best electrode and optimal machining parameters for machining AISI M2 steel. In one-dimensional optimization, for brass electrode, to maximize MRR value, the optimal machining parameters combination is A3TON1TOFF3 and to minimize EWR value, the optimal machining parameters combination is A1TON1TOFF2. For copper electrode, to maximize MRR value, the optimal machining parameters combination is A1TON1TOFF3 and to minimize EWR value, the optimal machining parameters combination is A1TON3TOFF1. In multidimensional optimization, for the copper electrode, the optimal machining parameters combination was A1TON1TOFF3 and for the brass electrode, the optimal machining parameters combination is A3TON1TOFF3. It could be concluded that EDM machining of HSS (AISI M2) by using the copper electrode will give the best results and the optimal machining parameters combination is A1TON1TOFF3. Yet, further research needs to be conducted to study these results and analyze machining process effectiveness in terms of cost and process sustainability, i.e. environmental impact. This research has both theoretical and practical implications.

Logistics is one of the major driver of supply chain (SC) and its performance has significant impact on overall SC performance. Due to advancement in technology, collecting, storing, and analysis of data is now become easy. Nowadays organizations are competing each other of the basis of their logistics performance. The purpose of this paper is to propose a prototype of decision support system based on Fuzzy - AHP (FAHP) that incorporate decision makers and managers' knowledge and experience and evaluate overall logistics performance.

Organizations and entrepreneurs use innovation-mapping models to map their innovation patterns, detect dominant innovation types and explore new areas where they can focus their future innovation projects at. The objective of this paper is to propose a new mapping model that can map more innovation areas or dimensions and overcome the gaps existing in the current mapping models. This new model will contribute to the advancement of the knowledge in innovation classification and mapping, which in turn shall enhance knowledge in engineering education scope. The analysis of the current innovation mapping models revealed many gaps and potential improvement areas. For example, current mapping models are not capable to map all combinations of innovation dimensions, and they are not capable to show the sustainability attributes of the innovation as well. To propose a new innovation-mapping model, a literature review on the innovation types, and the currently used classification and mapping models was conducted. The area of innovation for sustainability was also discussed and analyzed, and based on that, a new mapping model was proposed. The new proposed model is capable to model one, two, three, and four-dimensional innovation types. It is also capable to map the degree of novelty and sustainability attributes in innovations. For future research, it is suggested to test the validity and ease of use of the proposed model in different industries.

Many organizations over the world considers patent analysis as a useful tool in identifying and acquiring new technologies, understanding the relation between different technologies in order to maximize their profit, evaluating patents' values, monitoring their competitors, managing their R&D portfolio, managing their human resources, licensing in-out technologies, and indicating which firms are about to enter or leave a technology. The objective of this paper is to bring the attention of educational institutions, faculty members, undergraduate students, and the researchers to the importance of the areas of patents and patenting process in engineering education. Review the used patent analysis and patent technology indicators and its applications to identify the potential research gaps. Explain the most recent developments in the patents' offices criteria, patenting principles, investigate sustainability role in the patenting process or patents analysis, and then propose a framework to incorporate sustainability criteria in the patenting process, and patent analysis processes. During this literature review, and after excluding all irrelevant publications, 53 publications reviewed in this paper for the period from 1987 to 2017. Patent system, patent analysis, patent technology indicators, and patenting process topics found to be one of the important and viable information sources, which should be an integral part in undergraduate and postgraduate educational strategic and curriculums' plans. Potential research gaps identified and future work suggested. Authors in this paper proposed a framework to incorporate sustainability concept in the patenting process, and the patent analysis. The proposed framework argue that sustainability criteria should be incorporated simultaneously in the patenting process during patent's application processing along with patenting policies. Moreover, same criteria should be considered during patent analysis. The main limitation of this work that it is provide a strategic view framework. Therefore, future research directions should be focused to derive the right operational methods/models for sustainability criteria incorporation in the patents applications evaluation as well as patent analysis techniques.

Manufacturing systems is one of the main pillars of the global economy and there is a continuous effort to make it more advanced, more sustainable, and more user-friendly. Toward this direction, the concept of computer-integrated manufacturing (CIM) invented. CAD-CAPP-CAM-CNC systems' integration considered as prerequisite for CIM to be exist. Data exchange format was one of the main systems' integration obstacles due to the lack of standardization, or in other words, lack of effective data exchange format. Therefore, ISO organization started STEP 10303(Standard for the Exchange of Product Data model) project in 1994 to create a generic standard for data exchange on different levels. STEP-NC (or ISO 14649) developed specifically for data exchange between CAD, CAM, CAPP, CNC and other corporate levels. Many researchers stated that STEP-NC format is the future solution to overcome all data exchange obstacles as it has provide a bi-directional information flow and offer the possibility of dynamic changes on the design models. However, attempts to embed STEP-NC format in manufacturing systems still at the early stage. On the other hand, in last three decades, the global warming theory reported and many researchers focused their efforts to study the sustainability concept. The objective of this paper is to prove the novelty of having an integrated system by means of STEP-NC format for data exchange and in same time generating plans by considering sustainability principles. 59 papers reviewed for the period between 2001 and 2017. Authors were able to prove the novelty of the aforementioned approach as well as finding many other research gaps.

Electro discharge machining (EDM) process need to be optimized when a new material invented or even if some process variables changed. This process has many variables and it is always difficult to get the optimum set of variables by chance. Therefore, an optimization process need to be conducted considering different combinations of machining parameters as well as other variables even if the process were optimized for a certain set of variables. Optimization of the EDM process for machining stainless steel 304 (SS304) (ASTM A240) was studied in this paper. Signal-to-noise ratio (S/N) was calculated for each performance measures, and multi response performance index (MRPI) was generated using fuzzy logic inference system. Optimal machining parameters for machining SS304 materials were identified, namely current 10, pulse on time 60 μs, and pulse off time 35 μs. Analyses of variances (ANOVA) method was used as well to see which machining parameter has significant effect on the performance measures. The result of ANOVA indicates that pulse off time and current are the most significant machining parameters in affecting the performance measures, with the pulse off time being the most significant parameter.

Quality of hot and cold merchandisers are an important tool if food is to be held and displayed properly to entice consumers to buy and to drive food to go sale. In this paper, QFD tool used to translate the voice of the customer to technical aspects in order to set an action plan to improve the double door cold merchandising unit. It was found that eliminating the moisture from the door glass, sliding door mechanism durability, and light system durability are the most important requirements, while increasing insulation efficiency, anti moisture solutions, using LED tubes, and electricity fluctuation solution, was found to be the most important technical descriptors. HOQ presented in this work contributed in prioritising company's R&D directions. Further research efforts will be continuing the balance steps of QFD process, other future work suggestions could be using QFD tool to assess voice of the customers for other products.