The use of process simulation methods in support of organisational learning in availability contracting

Traditional business models in the aerospace industry are based on a conventional supplier to customer relationship based on the design, manufacture and subsequent delivery of the physical product. Service provision, from the manufacturer's perspective, is typically limited to the supply of procedural documentation and the provision of spare parts to the end user as the product passes through the latter stages of its intended lifecycle. Challenging economic and political conditions have resulted in end users re-structuring their core business activities, particularly in the defence sector. This has resulted in the need for original equipment manufacturers (OEMs) to integrate and manage support service activities in partnership with the customer to deliver platform availability. This improves the probability of commercial sustainability for the OEM through shared operational risks while reducing the cost of platform ownership for the customer. The need for OEMs to evolve their design, manufacture and supply strategies by focusing on customer requirements has revealed a need for reconstruction of traditional internal behaviours and design methodologies. Application of organisational learning is now a well recognised principle for innovative companies to achieve long term growth and sustained technical development, and hence, greater market command. It focuses on the process by which the organisation's knowledge and value base changes, leading to improved problem solving ability and capacity for action. From the perspective of availability contracting, knowledge and the processes by which it is generated, used and retained, become primary assets within the learning organisation. This paper will introduce the application of digital methods to asset management by demonstrating how the process of learning can benefit from a digital approach, how product and process design can be integrated within a virtual framework and finally how the approach can be applied in a service context.

Extracting S-matrix poles for resonances from numerical scattering data: Type-II Pade reconstruction

We present a FORTRAN 77 code for evaluation of resonance pole positions and residues of a numerical scattering matrix element in the complex energy (CE) as well as in the complex angular momentum (CAM) planes. Analytical continuation of the S-matrix element is performed by constructing a type-II Pade approximant from given physical values (Bessis et al. (1994) [421: Vrinceanu et al. (2000) [24]; Sokolovski and Msezane (2004) [23]). The algorithm involves iterative 'preconditioning' of the numerical data by extracting its rapidly oscillating potential phase component. The code has the capability of adding non-analytical noise to the numerical data in order to select 'true' physical poles, investigate their stability and evaluate the accuracy of the reconstruction. It has an option of employing multiple-precision (MPFUN) package (Bailey (1993) [451) developed by D.H. Bailey wherever double precision calculations fail due to a large number of input partial waves (energies) involved. The code has been successfully tested on several models, as well as the F + H-2 -> HE + H, F + HD : HE + D, Cl + HCI CIH + Cl and H + D-2 -> HD + D reactions. Some detailed examples are given in the text.

A Competence-Based Post-Disaster Reconstruction Process: Findings from Sri Lanka

As natural disasters continue to escalate in frequency and magnitude, NGOs are faced with numerous barriers as they attempt to implement post-disaster reconstruction (PDR) projects. In many cases, a lack of competency in key areas leads to a reduction in overall project success. This paper utilizes the competency-based framework of von Meding et al. (2010) as the starting point of its inquiry. In this context, a leading NGO responsible for the implementation of reconstruction and rehabilitation in Sri Lanka following the Asian Tsunami has been investigated in depth using a causal mapping interview procedure with key project staff. The combined barriers within this organization’s PDR operations have been identified and measured and solutions articulated. The study found that within this organization key objectives were to achieve the ‘build back better’ mantra and to effectively plan interventions in advance. The primary barriers to successful reconstruction were identified as the high turnover rate of humanitarian staff and a poor level of communication and co-operation between agencies. An essential strategy employed to combat these barriers is the consideration of staff capabilities, which links us back to competence-based theory. The results are highly valuable in the context of an ongoing wider research study on competence within humanitarian organizations.