Use of Digital Manufacturing to Improve Management Learning in Aerospace Assembly

The primary goal of this work is to quantify any bene?ts that the use of digital manufacturing methods can offer when used upstream from production, for manufacturing process design, and tool development. Learning at this stage of product development is referred to as management learning. Animated build simulations have been used to develop build procedures and tooling for a panel assembly for the new Bombardier CRJ1000 (Canadair Regional Jet, 100 seat). When the jig format was developed, its simulated performance was compared to that of current CRJ700/900 panel builds to identify and quantify any improvements in terms of tooling cost and panel build time. When comparing like-for-like functions between existing CRJ700/900 (Canadair Regional Jet, 70/90 seat) and the
CRJ1000 tooling, it was predicted that the digitally assisted improvements had brought about a 4.9% reduction in jig cost. An evaluation of the build process for the CRJ1000 uplock panel predicted a 5.2% reduction in the assembly time. In addition to the improvement of existing tooling functions, new jig functionality was added so that both the drilling and riveting functions could be carried out in a single jig for the new RJ1000 panel.

Dynamic Knowledge Creation Through Value Management Teams

With the intention of introducing unique and value-added products to the market, organizations have become more conscious of how to best create knowledge as reported by Ganesh Bhatt in 2000 in 'Information dynamics, learning and knowledge creation in organizations'. Knowledge creation is recognized as having an important role in generating and sustaining a competitive advantage as well as in meeting organizational goals, as reported by Aleda Roth and her colleagues in 1994 in 'The knowledge factory for accelerated learning practices.' One of the successful ingredients of value management (VM) is its utilization of diverse knowledge resources, drawing upon different organizational functions, professional disciplines, and stakeholders, in a facilitated team process. Multidisciplinary VM study teams are viewed as having high potential to innovate due to their heterogeneous nature. This paper looks at one of the VM workshop's major benefits, namely, knowledge creation. A case study approach was used to explore the nature, processes, and issues associated with fostering a dynamic knowledge creation capability within VM teams. The results indicate that the dynamic knowledge creating process is embedded in and influenced by managing team constellation, creating shared awareness, developing shared understanding, and producing aligned action. The catalysts that can speed up the processes are open dialogue and discussion among participants. This process is enhanced by the use of facilitators, skilled at extracting knowledge.

An empirical study of green supply chain management practices amongst UK manufacturers

Purpose: The purpose of this paper is to examine the extent and nature of greening the supply chain (SC) in the UK manufacturing sector; and the factors that influence the breadth and depth of this activity.

Design/methodology/approach: Based on the findings from a sample of manufacturing organisations drawn from the membership of The Chartered Institute for Purchasing and Supply. Data are collected using a questionnaire, piloted and pre-tested before distribution with responses from 60 manufacturing companies.

Findings: On average manufacturers perceive the greatest pressure to improve environmental performance through legislation and internal drivers (IDs). The least influential pressures are related to societal drivers and SC pressures from individual customers. Green supply chain management (GSCM) practices amongst this “average” group of UK manufacturing organisations are focusing on internal, higher risk, descriptive activities, rather than proactive, external engagement processes. Environmental attitude (EA) is a key predictor of GSCM activity and those organisations that have a progressive attitude are also operationally very active. EA shows some relationship to legislative drivers but other factors are also influential. Operational activity may also be moderated by organisational contingencies such as risk, size, and nationality.

Research limitations/implications: The main limitation to this paper is the relatively small manufacturing sample.

Practical implications: This paper presents a series of constructs that identify GSCM operational activities companies to benchmark themselves against. It suggests which factors are driving these operational changes and how industry contingencies may be influential.

Originality/value: This paper explores what is driving environmental behaviour amongst an “average” sample of manufacturers, what specific management practices take place and the relationships between them.

Keywords: Manufacturing industries, Environmental management, Supply chain management, Sustainable development, United Kingdom
Paper type: Research paper

Sustainable Value Creation among Companies in the Manufacturing Sector

In this paper, we present empirical results of a study on the creation of Sustainable Value among European manufacturing companies. As sustainable development is a future oriented concept we assess the use of environmental resources in companies in the light of the EU15 performance targets for 2010. By using the Sustainable Value approach and based on publicly available company data we measure in monetary terms how individual companies perform vis-a-vis the 2010 performance targets already today. This shows the specific exposure and vulnerability of companies to more stringent policy regimes, and allows meaningful comparisons between both companies and sectors.

The role of operations management in public sector policy and practice alignment: a local government analysis

In responding to the demand for change and improvement, local government has applied a plethora of operations management-based methods, tools and techniques. This article explores how these methods, specifically in the form of performance management models, are used to improve alignment between central government policy and local government practice, an area which has thus far been neglected in the literature. Using multiple case studies from Environmental Waste Management Services, this research reports that models derived in the private sector are often directly ‘implanted’ into the public sector. This has challenged the efficacy of all performance management models. However, those organisations which used models most effectively did so by embedding (contextualisation) and extending (reconceptualisation) them beyond their original scope. Moreover, success with these models created a cumulative effect whereby other operations management approaches were probed, adapted and used.

An Integration Methodology for Automated Recurring Cost Prediction using Digital Manufacturing Technology

The need to account for the effect of design decisions on manufacture and the impact of manufacturing cost on the life cycle cost of any product are well established. In this context, digital design and manufacturing solutions have to be further developed to facilitate and automate the integration of cost as one of the major driver in the product life cycle management. This article is to present an integration methodology for implementing cost estimation capability within a digital manufacturing environment. A digital manufacturing structure of knowledge databases are set out and the ontology of assembly and part costing that is consistent with the structure is provided. Although the methodology is currently used for recurring cost prediction, it can be well applied to other functional developments, such as process planning. A prototype tool is developed to integrate both assembly time cost and parts manufacturing costs within the same digital environment. An industrial example is used to validate this approach.

Prediction of integral type failures in semiconductor manufacturing through classification methods

Smart management of maintenances has become fundamental in manufacturing environments in order to decrease downtime and costs associated with failures. Predictive Maintenance (PdM) systems based on Machine Learning (ML) techniques have the possibility with low added costs of drastically decrease failures-related expenses; given the increase of availability of data and capabilities of ML tools, PdM systems are becoming really popular, especially in semiconductor manufacturing. A PdM module based on Classification methods is presented here for the prediction of integral type faults that are related to machine usage and stress of equipment parts. The module has been applied to an important class of semiconductor processes, ion-implantation, for the prediction of ion-source tungsten filament breaks. The PdM has been tested on a real production dataset. © 2013 IEEE.

Semi batch learning with store management using enhanced conjugate gradient

This paper explores the performance of sliding-window based training, termed as semi batch, using multilayer perceptron (MLP) neural network in the presence of correlated data. The sliding window training is a form of higher order instantaneous learning strategy without the need of covariance matrix, usually employed for modeling and tracking purposes. Sliding-window framework is implemented to combine the robustness of offline learning algorithms with the ability to track online the underlying process of a function. This paper adopted sliding window training with recent advances in conjugate gradient direction with application of data store management e.g. simple distance measure, angle evaluation and the novel prediction error test. The simulation results show the best convergence performance is gained by using store management techniques. © 2012 Springer-Verlag.