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Reconfigurable Manufacturing Systems (RMS) have gained attention in the aerospace industry in the past years, as post-pandemic context shows drastic production capacity changes and new environmental regulations to which it must adapt quicker than before to maintain competitiveness. Nevertheless, current RMS design methods have not thoroughly considered this industry specificities, nor industrial resources requirements in the current concurrent design practice. These limitations have been identified in several recent research works. Ontology-based Engineering (OBE) systems can stand overly complex collaborative design processes involving multidisciplinary stakeholders and various digital tools, integrating different levels of decision. Models for Manufacturing (MfM) is an OBE methodology aiming to enable industrial design and decision-making in manufacturing by preserving the company knowledge in ontology models, usable as knowledge base to generate and integrate the aircraft and manufacturing systems design. This paper presents an MfM application for RMS design in aerospace, introducing innovative design concepts that allow implementing RMS in a collaborative engineering process of an aerospace product. An implementation is shown designing the RMS of a model aircraft family to illustrate the concepts introduced and considerations are given to transfer this knowledge base into an OBE system to support complex real-life applications. [ABSTRACT FROM AUTHOR]

Empirical engineering knowledge (EEK), a specific technical know-how about solving engineering problems, is frequently accumulated and reused in this era of mass innovation and knowledge-driven economy. Since EEK is abidingly evolving because of the intense business competitions, continual technical renovations and wide industrial concern, it’s a new challenge both in theories and applications of knowledge management to analyse EEK evolution and its motivations. This paper proposes a novel approach to tackle this non-trivial issue. Based on the constructed domain hierarchy and EEK networks, EEK clusters are grouped and represented with populations, latent topics and distributions. Then four kinds of evolutional patterns are defined and recognised from the EEK clusters in neighbouring time intervals. The evolutional motivations of these patterns are discovered from the important evolutional events, with the proposed abductive reasoning algorithm. This paper also integrates all techniques, and implements a knowledge management system EEK-KEAS in computer-aided design (CAD), a typical engineering field. Experimental result shows that EEK-KEAS operations well in revealing the evolutional motivations of CAD EEKs, and outperforms the former approaches in feasibility and effectiveness, thereby opening up a novel way for further understanding the evolution of EEK. [ABSTRACT FROM AUTHOR]

Cost engineering capabilities are becoming increasingly important for the competitiveness of industrial firms, especially for engineer to order products (ETOPs). Despite this relevance, the literature on the use of advanced data-driven methodologies, such as machine learning (ML), for early cost estimation (CE) of ETOPs is quite sparse. Furthermore, ML has still seen little use in real industrial applications due to several challenges. Accordingly, the objective of this paper is threefold: (a) to develop a solid early CE approach for ETOPs, including feature selection; (b) to investigate the benefits of adopting ML for ETOPs' CE; (c) to identify how ML can be introduced into real industrial context with little knowledge on ML. Long action research has been carried out with a large industrial company that produces Oil & Gas ETOPs. We observed how ML facilitates the exploration of the relationships between the choices of early design stages and the CE. ML algorithms also allowed to both capture the high variability of the data and test different combinations of cost drivers in very effective ways. The project resulted in an accurate CE framework with an iterative feature selection process and an approach for introducing ML into a real industrial context. [ABSTRACT FROM AUTHOR]

This paper proposes a mathematical programming technique to optimize the product development process. Using a concurrent engineering approach, the paper presents a formulation that maps the different stages of product development. The decision variables of these stages are then determined simultaneously. While the Quality Function Deployment Technique (QFD) is based on a qualitative sequential approach, this paper proposes a holistic quantitative approach to concurrent product-process optimization. The mathematical programming technique is applied to the first two stages of product development: the optimization of customer satisfaction and the product's design. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy-based assessment model to evaluate system reliability of a labour-intensive manufacturing system with repair actions. Due to the uncertainty in human performance, labour-intensive manufacturing systems must determine the capacity of each labourer in order to accurately characterise the performance of the systems. Therefore, we model such a manufacturing system as a fuzzy multi-state network in order to characterise the labourers’ influence on workstation performance. First, the workstation reliability is defined according to the loading state by three fuzzy membership functions, namely ‘under loading’, ‘normal loading’ and ‘over loading’, respectively. The system reliability is subsequently evaluated with fuzzy intersection operations in terms of these workstation reliabilities. Thus, the system reliability is defined as a fuzzy membership function to assess whether the manufacturing system performance is sufficient to satisfy the demand reliably. A case study of a footwear manufacturing system is illustrated to explain the proposed model. Furthermore, we apply the proposed model to a non-labour-intensive manufacturing network in order to validate the applicability to this class of systems. [ABSTRACT FROM PUBLISHER]

In order to satisfy the current market demands for shorter lead-time and high quality products manufacturing enterprises have to integrate their design, production and quality assurance functions. In a computerized environment these functions are manifested in CAD, CAM and AVI respectively. In the recent past, much success has been achieved in integrating CAD and CAM. It is widely accepted that feature recognition systems, both 2D and 3D, have been one of the main contributors to CADCAM integration. However the existing feature recognition systems could not link CADCAM and AVI and hence could not close the manufacturing loop that ensures the production of designer intended features. This is mainly because the input formats of existing feature recognition systems and AVI systems have been different in format and structure. The system described in this paper attempts to redress this deficit at least partially by using a monochrome bitmap as a generic input, to which both CAD models and vision images could be converted. Hence the input to the system takes a form of third angle orthographic views, however, without hidden lines in order to facilitate dealing with vision images. This, in turn, augments difficulty faced in recognizing features. To overcome this difficulty, the help of evolutionary computing and artificial intelligence is sought in this system. This paper outlines the basis of a 2D feature recognition system that uses artificial neural networks along with a chain code method for eliciting feature information from monochrome bitmap of either vision images or CAD inputs hence providing a generic framework to integrate CADCAM and AVI. With further improvement to deal with geometry of the features, annotations and symbols this system could also help to salvage the massive store of engineering knowledge that exists in 2D form. [ABSTRACT FROM AUTHOR]

The use of the Integrated Integration Definition Language 0 (IDEF) descriptive model or similar tools alone in the analysis of complicated processes like the mould-making process usually encounters difficulties due to the complexity of process. A quantitative analysis model thus seems necessary to supplement the IDEF0 tool for better modelling and simulation of complicated processes. The paper proposes to integrate the IDEF0 tool with the coloured Petri nets (CPN) tool for systematic analysis of complicated processes. It introduces an effective modelling and simulation language-hierarchical timed CPN-based workflow nets (HTCPNWF-nets). The rules for translating IDEF0 into HTCPNWF-nets have been developed. After mapping the IDEF0 model onto HTCPNWF-nets, several performance analyses can be achieved by simulation of HTCPNWF-nets model. The proposed methodologies have been successfully applied to the mould-making process. The paper presents the rationales and current progress of the proposed methodologies. [ABSTRACT FROM AUTHOR]

Engineering knowledge is an important asset of industrial companies. The present research focuses on design activity knowledge and it attempts to develop effective ways to capture this operational knowledge from the design events monitored during the design process. A design activity is defined as a sequence of meaningful design operations carried out by designers to advance the design from its current state to the new state. The paper proposes a design activity knowledge acquisition (DAKA) framework that extracts designers’ design activity knowledge from the computer-aided design (CAD) operation event data obtained through commercial CAD systems. DAKA is composed of a product model roadmap for capturing the trajectory of designers’ design moves and a function-based design operation-mining algorithm for extracting meaningful design operations from CAD event databases. DAKA has been evaluated through case studies using real CAD operation event data as well as computer-generated synthetic data. In this paper, the details of the DAKA framework are described and a case example involving automotive door design is presented to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Recent literature about quality control has investigated the continuous surveillance of the ratio of two normal random variables under the assumption of no measurement error. However, in practice, measurement errors always exist in quality control applications and may considerably affect the performance of control charts. In this paper, the performance of the Shewhart-RZ control chart is investigated in the presence of a measurement error and modelled by a linear covariate error model. Several figures and tables are generated and commented to show the statistical performance of the Shewhart-RZ control chart for different sources of the measurement error. Two examples illustrate the use of this chart on a quality control problem simulated from the food industry and a real industrial case from a plant treating batteries for recyclement. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of ontologies in the context of product lifecycle management (PLM) is gaining importance and popularity, while at the same time it generates a lot of controversy in discussions within scientific and engineering communities. Yet, what is ontology? What challenges have been addressed so far? What role does ontology play? Do we really need ontology? These are the core questions this paper seeks to address. We propose to conduct a comprehensive study of the concept of Ontology firstly in its domain of origin, Philosophy, and secondly in information science. Based on the understanding of this concept and an in-depth analysis of the state of the art, seven key roles of ontology are defined. These roles serve as a framework describing the general state of research on the use of ontologies in the context of PLM. [ABSTRACT FROM AUTHOR]

Nowadays, since the resources of remanufacturing are the ‘cores’, the uncertainty in quantity and quality of the ‘cores’ is an obstacle in remanufacturing engineering. To solve this problem, production management and design for remanufacturing have been discussed in the former studies. However, the current remanufacturing mode, which is carried out in the end of life cycle, is reactive. To delimit the uncertainty of ‘cores’, the concept of proactive remanufacturing is presented in this paper. And one issue is to identify the proactive remanufacturing timing. In the beginning, the reactive remanufacturing timing and proactive remanufacturing timing are introduced. Then, to characterise the remanufacturability of components, the concept of residual strength is proposed. To identify the proactive remanufacturing timing, the mathematical model is established based on the residual strength, remanufacturing value and technical feasibility. Based on this model, the timing determination method in proactive remanufacturing is presented and expanded. Finally, to validate this method, the proactive remanufacturing timing of engines is determined by analysing the crankshaft. As a consequence, in the proactive remanufacturing mode, the remanufacturing rate of product might be increased. Thus, the proactive remanufacturing could provide a new perspective in future remanufacturing engineering. [ABSTRACT FROM PUBLISHER]

Engineering-oriented empirical tacit knowledge (ETK) is a kind of tacit knowledge originated from domain expert’s experience combined with practice cases and scenarios. It is an important source of organisation knowledge. However, due to operational and technical obstacles, this kind of knowledge is not sufficiently harnessed and put into practical use. To deal with this problem, a novel two-stage acquisition method is proposed in this paper. The acquisition method consists of two phases, the stage from ETK in the mind of expert to ETK in initial state, and the stage from ETK in initial state to structured ETK. It constructs a complete tacit knowledge acquisition process from the domain expert’s experience to the structured tacit knowledge. The objective is achieved by taking the following procedures: Firstly, present the concept of engineering-oriented ETK and a five-dimension representation model of ETK. Secondly, construct a two-stage ETK acquisition framework. Finally, describe an engineering decision case to validate the feasibility of the proposed approach. Satisfactory results are reached for the study. [ABSTRACT FROM PUBLISHER]

Due to the high cost of equipment, most semiconductor wafer fabrication facilities process both regular production lots which are shipped to customers and engineering lots that support product and process development efforts. The different objectives of the engineering and production organisations render the problem of allocating equipment capacity between these different types of lots a difficult and often contentious problem. In this paper we explore the impacts of several different policies for allocating resources to production and engineering work on the shop floor using a scaled-down simulation model of a wafer fabrication facility. Our results indicate that the availability and flexibility of engineering resources can affect the performance of scheduling policies in quite different ways. We conclude that this problem needs to be viewed in a broader context than that of a shop floor scheduling issue, including the level of available engineering resources, their degree of cross-training and the manner in which engineers are allocated to different projects. [ABSTRACT FROM AUTHOR]

The drive to maximize the potential benefits of decision support systems continues to increase as industry is continually driven by the competitive needs of operating in dynamic global environments. The more extensive information support tools which are becoming available in the PLM world appear to have great potential but require a substantial overhead in their configuration. However, sharing information and knowledge in cross-disciplinary teams and across system and company boundaries is not straightforward and there is a clear need for more effective frameworks for information and knowledge sharing if new product development processes are to have effective ICT support. This paper presents a view of the current status of manufacturing information sharing using light-weight ontologies and goes on to discuss the potential for heavyweight ontological engineering approaches such as the Process Specification Language (PSL). It explains why such languages are needed and how they provide an important step towards process knowledge sharing. Machining examples are used to illustrate how PSL provides a rigorous basis for process knowledge sharing and subsequently to illustrate the value of linking foundation and domain ontologies to provide a basis for multi-context knowledge sharing. [ABSTRACT FROM AUTHOR]

This paper discusses an approach to evaluate the assemblability of a product according to its assembly sequence. A concept called Sensitive Tolerance in Assembly is proposed and its influence on the assembly is investigated. The approach using a transformation matrix is proposed to determine the geometric deviations of mating features caused by the tolerance and assembly clearance, and the resulting propagation and accumulations in the different assembly sequences. An example is given to illustrate the approach to derive the relative assemblability of a product for comparing different assembly sequences. [ABSTRACT FROM AUTHOR]

The increasing complexity of enterprise systems requires a more advanced analysis of the representation of services expected than is currently possible. Consequently, the specification stage, which could be facilitated by formal verification, becomes very important to the system life-cycle. This paper presents a formal modelling approach, which may be used in order to better represent the reality of the system and to verify the awaited or existing system's properties, taking into account the environmental characteristics. For that, we firstly propose a formalization process based upon properties specification, and secondly we use Conceptual Graphs operations to develop reasoning mechanisms of verifying requirements statements. The graphic visualization of these reasoning enables us to correctly capture the system specifications by making it easier to determine if desired properties hold. It is applied to the field of Enterprise modelling. [ABSTRACT FROM AUTHOR]

Product configuration design is of critical importance in design for mass customization. This paper will investigate two important issues in configuration design. The first issue is requirement configuration and a dependency analysis approach is proposed and implemented to link customer groups with clusters of product specifications. The second issue concerns the engineering configuration and it is modelled as an association relation between clusters of product specifications and configuration alternatives. A novel methodology and architecture are proposed for accomplishing the two configuration tasks and bridging the gap between them. This methodology is based on integration of popular data mining approaches (such as fuzzy clustering and association rule mining) and variable precision rough set. It focuses on the discovery of configuration rules from the purchased products according to customer groups. The proposed methodology is illustrated with a case study of an electrical bicycle. [ABSTRACT FROM AUTHOR]

Robotic manufacturing systems have proven to be an effective solution for modern manufacturing enterprises to deal with increasing in customer demands and market competition. However, these systems may be unable to completely satisfy user requirements because of the difference between user and design perspectives. Thus, designing robotic manufacturing systems requires iterative processes that significantly increase development costs and lead time. A user-customised design approach is needed that enables users to customise robotic manufacturing systems as well as alleviate the burden on designers of eliciting user requirements. However, most users may not be able to customise their systems because of a lack of engineering knowledge. The authors propose a knowledge-based engineering approach to aid users in customising the architectures of robotic manufacturing systems. Two models — an ontological knowledge model and a multi-attribute decision-making model — are defined and integrated in the proposed KBE architecture definition method. A rule-based reasoning process is proposed in the ontological knowledge model based on explicit semantic descriptions of users' unstructured or semi-structured requirements and the components of robotic manufacturing systems, which infers the possible architecture of the required system. The MADM model is adopted to evaluate the architecture alternatives to determine the optimal solution. [ABSTRACT FROM AUTHOR]

This paper presents a new tolerance design theory—simultaneous tolerancing— which works in the concurrent engineering context. After stating the need to develop a simultaneous tolerancing theory by showing the shortcomings of conventional tolerancing technique, the concept of simultaneous tolerancing is given, and its elements are briefly presented. Then we focus our attention on the development of a general mathematical model of optimal tolerancing supporting concurrent engineering. Two commonly used models, worst-case and statistical, are discussed in detail. Next, a method of 'interim tolerances', which help to determine an appropriate machining process without using functional tolerances, is proposed. The simultaneous tolerancing theory presented in this paper permits of determining directly optimal machining tolerances in product design, reducing the manufacturing cost and improving the quality of products. Finally, an example is given, showing that the proposed theory is feasible in practice. [ABSTRACT FROM AUTHOR]

Technological forecasting is located in technological space for a certain engineering domain and is the first step in the research and development of a new technology. There are many techniques already developed for technological forecasting like extrapolation of trends, heuristics forecasting by expert e.g. Delphi method. etc. The morphological method (MM) is used to describe a technique for identifying, indexing, counting and parametrizing the collection of all possible devices to achieve a specified functional capability. This is not a forecasting per se, but it is a useful organizing tool, a sourer of insights and a starting point for further analysis by other methods, Milačié (1976). In the paper we expand the capabilities of MM using artificial intelligence (AI) principles. The AI production system has a global data base, a set of production rules and a control system. Special attention is paid to control strategy developing searching techniques in order to distinguish the explicit local knowledge about how to proceed toward a goal from any state from the implicit global knowledge of the complete solution. Some practical examples are also shown. [ABSTRACT FROM AUTHOR]

This is the first of two papers describing an approach to assessing the effectiveness of production control systems in defined company types. A method of classification according to production control complexity is developed, leading to the definition of six basic company classifications within the engineering batch-manufacturing sector. It is proposed that these groups should form the basis for a standardized approach to system design; this will be discussed further in the second paper. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tests were run with high strength thermal-resistant work materials selected by surveying U.S. aircraft engineering companies to find representative types of materials presenting problems in conventional machining. Each material tested had two different heat treatment procedures. Tests were conducted in orthogonal and conventional turning, in milling and in drilling operations using different methods of workpiece heating. Information was obtained on tool life--cutting speed relationships, tool temperatures and forces, chip formation and related quantities for a range of work temperatures. Metallographic studies of hot-machined parts were carried out and the effects of the process on workpiece geometry are discussed. Assessment of workpiece heating methods will be the subject of a further paper. [ABSTRACT FROM AUTHOR]

One of the problems which occupies the work study engineer is that of determining the number of observations necessary in order to estimate the work content of a job with a prescribed accuracy. A new equation is presented for this purpose. [ABSTRACT FROM AUTHOR]

Scheduling algorithms play an important role in manufacturing systems as a means of meeting customer demands. On the other hand, fuzzy logic, which has been successfully implemented in many engineering applications, including the recent work of Vanegas and Labib (2001a, b), has an ability to produce a more gradual transition. This paper presents an algorithm for transforming maintenance data to shop floor information. These shop floor data are then used via a fuzzy-logic based scheduling algorithm to determine optimal production systems control policies. The frequency of breakdowns and the mean number of parts required are used as inputs to the fuzzy logic controller. These inputs are transformed to the mean part arrival rate. The output is then fed to the scheduling algorithm. Finally, the optimal batch size is calculated. The algorithm is demonstrated with simulation. [ABSTRACT FROM AUTHOR]

Ever since the plus/minus limits on dimensions first started to appear on engineering drawings in the early 1900s, tolerances have been one of the most important issues for every engineer involved in the product realization processes. In particular, with the advancement of computers and CAD/CAM techniques in the 1970s, the tolerance-related issues have continuously drawn the attention of many researchers since then. As a result, a tremendous number of research articles have been published over the last 30 years. This paper aims at a comprehensive state-of-the-art review on various tolerancing issues in design and manufacturing. However, due to the overwhelming number of existing research publications, any reviews on tolerancing issues could by no means be exhaustive. Rather, this review attempts to provide the reader with a view toward a balanced understanding of the various problems in tolerancing by presenting some typical research work for each of the classified fields, and tries to draw the potential research directions in the future. [ABSTRACT FROM AUTHOR]

The paper presents the concepts and steps required to synthesize a correct control implementation for discrete manufacturing systems, starting from Grafcet specifications. A formal framework implementing the synthesis steps is also presented and illustrated with an example of a drilling system. [ABSTRACT FROM AUTHOR]

A key problem in large-scale concurrent engineering systems is the control and management of the large amount of information required. Constraint networks that are used to represent this information can become so large that structural and operational problems are difficult to identify and rectify. This paper proposes a new approach, called Meta-nets, to modelling large-scale concurrent engineering problems. Meta-nets provide an abstraction of an underlying constraint network. The overall result is a compact and powerful representation of the information flow. The abstraction and analysis of Meta-nets gives several important benefits. First, by dealing with network structure based on information flow, Meta-nets can assist in network navigation. Second, Meta-nets give the dependence relationships between variables in the concurrent engineering system. Third, Meta-nets effectively represent parallelism (i.e. the carrying out of activities separately but with some measure of cohesion), which is an essential characteristic of concurrent engineering. This can form the basis for parallel processing. Fourth and finally, Meta-nets provide a methodology for breaking large concurrent engineering networks into more manageable sub-networks. These advantages become especially important for large-scale concurrent engineering problems. [ABSTRACT FROM AUTHOR]

Concurrent Engineering Management is an engineering management philosophy for simultaneously addressing both the engineering as well as the operational management aspects of the product design process. In this paper, our focus is on the operational aspects of the Concurrent Engineering Management. For this purpose a quantitative decision making model is developed to manage both the cost and the schedule during the product development process. The proposed model is a fixed charge problem which is solved by a mixed integer programming algorithm. Furthermore, an example as well as a linear programming version of the model are presented. [ABSTRACT FROM AUTHOR]

The design of material flow systems is a multifaceted problem. The designer is required to process large amounts of information and make complex decisions concerning the design objectives. A design framework for building material flow system models has been developed by the authors to take key steps towards the management of design complexity. This paper addresses the issue of selecting and sequencing software tools for building material flow system models within a design environment that contains a variable set of design tools. Strategies for performing these tasks as well as their implementation are discussed. [ABSTRACT FROM AUTHOR]

The use of precedence diagrams and estimates of task times, as the only source of engineering information for assembly line balancing (ALB), is common to most ALB techniques developed to date. This paper presents a model which incorporates the information carried by an assembly chart (or a Gozinto chart) into the ALB problem in an attempt to consider engineering objectives such as improving work methods and work enrichment in the design of assembly lines. A multi-objective approach is developed which integrates the traditional objective of minimizing the idle time of the line with the objective that a minimum number of subassemblies should be handled at each workstation. [ABSTRACT FROM AUTHOR]

The success of future automated planning systems greatly depend on further advances in two areas: (a) enhanced product modeling systems capable of answering questions posed during the planning phase; and (b) techniques for representing and manipulating planning knowledge. The work reported in this paper, investigates the use of a feature-based approach for modeling engineering parts to support the product data requirements of an intelligent planning system, employing the frame-based and rule-based knowledge representation techniques from artificial intelligence research. The approach has been applied to the domain of rotational parts. [ABSTRACT FROM AUTHOR]

Measurements are carried out on engineering components and analyzed to check the conformity of the components to specification. This paper discusses different methods that are useful for assessing the errors on the dimensions, form and position of geometric features. A new approach called the median technique, which gives minimum values of errors is introduced. [ABSTRACT FROM AUTHOR]

This article presents a case study of the effect of engineering changes and demand uncertainty on material requirements planning (MRP) lot sizing. Much has been said on the various aspects of lot sizing for single-level and multi-level systems in MRP. Numerous heuristic have been developed and tested on problems with finite horizon and deterministic, time-varying demand. However, in practice, the hypothesis of a finite horizon and deterministic demand contains several inherent deficiencies. Indeed, the finite horizon assumption ignores that decisions are usually made on a rolling schedule basis. Moreover, lot-sizing decisions are based on uncertain information about future demand. Timing and quantity of future requirements are, at least partially, based on forecasts and hence imply forecast errors and the need for rescheduling. Finally, engineering changes can also lead to very high scrap costs and hence should he incorporated into the lot-sizing decisions. In this paper the influence of these factors on lot-sizing decisions is examined for a real life problem in a capacity that produces electronic components to be used in high technology telecommunication systems.

The paper describes the structure of an interactive manual data input programming system which was developed for drilling and which uses a 'shop floor oriented' language. This programming system incorporates 'cutting technology', to provide an unskilled machine operator with computer assistance in achieving optimum drilling conditions for a wide range of engineering materials, and has been designed to be used in conjunction with a microprocessor-based NC drilling system, the structure of which is also briefly described. [ABSTRACT FROM AUTHOR]

To sustain their competitive advantage in a highly competitive landscape, SMEs, in spite of their limited resources, need to effectively learn. The ability to access and successfully use knowledge is at the heart of absorptive capacity. The main purpose of this empirical study is to investigate the importance of awareness as an antecedent dimension of the concept of absorptive capacity of manufacturing SMEs from aerospace and advanced engineering industry in the UK. The study will also attempt to explore the impact of awareness on the other dimensions of absorptive capacity. Awareness is related to the importance, motivation and interest of learning and innovating. Our study, which focuses on internal processes adopts a mixed method approach and is based on the data collected from 43 SMEs. Our finding suggests that awareness as an antecedent dimension can play a vital role in helping SMEs to improve their knowledge-based resources through changes within their internal organisational and cognitive processes. [ABSTRACT FROM PUBLISHER]