Rahul Swarnkar

A framework for collaboration moderator services to support knowledge based collaboration

Knowledge sharing is a major challenge for collaborative networks and is essential to improve the productivity and quality of decisions taken by both collaborative networks and their member organisations. A critical aspect of effective knowledge sharing within virtual organizations (VOs) is the identification of the most appropriate knowledge for reuse or exploitation in a particular context, as this requires efficient tools and mechanisms for its identification, sharing or transfer. Additionally, partners need to be aware of when knowledge needs to be shared, the implications of doing so and when their decisions are likely to affect other partners within the collaboration. Therefore, tools and methods are needed for identification, acquisition, maintenance and evolution of knowledge and to support effective knowledge sharing which includes awareness of possible consequences of actions and increased awareness of other partner’s needs during the collaboration. The Collaboration Moderator Services (CMS) are designed to address these issues relating to knowledge based collaboration by providing a set of functionalities to raise users’ awareness of opportunities, problem areas and lessons learnt from and during collaborations. This paper presents the system architecture and specifications of the CMS within the context of the SYNERGY system, whose purpose is to offer interoperable service utilities to help enterprises plan, setup and run complex knowledge collaborations. The CMS are designed to support both individual organizations and collaborations as a whole throughout the VO lifecycle and the different functionalities provided by CMS to achieve this are discussed in this paper.

Design of synchronised supply chain: a genetic algorithm based six sigma constrained approach

Managing and optimising a supply chain requires an important link in the channel and synchronisation between its business partners. This paper suggests a methodology leading to the synchronisation of the business processes in a supply chain with the objective of minimising the total cost involved. The solution is constrained by a six sigma approach to ensure very high delivery probability within the customer specified delivery window. A mathematical formulation of the problem, inspired by its resemblance to the mechanical assembly tolerancing issues, is developed to relate the costs involved and the tolerances gained. A six sigma constrained Genetic Algorithm (GA) based heuristic is proposed to achieve the optimal solution of the problem. Computational experiments performed on ten randomly generated problems representing real life supply chains, reveal that the proposed GA based heuristic performs well with respect to solution accuracy and efficiency. Towards the end, a detailed analysis of the proposed approach to comprehend its usefulness as a decision-making tool is provided to aid the supply chain experts.

Generating rules from data mining for collaboration moderator services

A Moderator is a knowledge based system that supports collaborative working by raising awareness of the priorities and requirements of other team members. However, the amount of advice a Moderator can provide is limited by the knowledge it contains on team members. The use of data mining techniques can contribute towards automating the process of knowledge acquisition for a Moderator and enable hidden data patterns and relationships to be discovered to facilitate the moderation process. A novel approach is presented, consisting of a knowledge discovery framework which provides a semi-automatic methodology to generate rules by inserting relationships discovered as a result of data mining into a generic template. To demonstrate the knowledge discovery framework methodology an application case is described. The application case acquires knowledge for a Moderator to make project partners aware of how to best formulate a proposal for a European research project by data mining summaries of successful past projects. Findings from the application case are presented.

Implementing collaboration moderator service to support various phases of virtual organisations

Research into moderators, which support collaborative teams by proactively making team members aware of actions or potential problems which may affect them, began in the 1990s, in the context of supporting collaborations during concurrent engineering projects. This paper provides a background to the evolution of moderators and explores their role in supporting virtual organisations. A collaboration moderator (CM) is an evolution of earlier moderators and is capable of behaving differently for different types of users and therefore caters for the varying requirements of individual users depending on the roles they have in the collaborations. This paper describes the architecture and components of a CM from an implementation perspective. Prototype CMs have been developed during the EU-funded SYNERGY project, and two use cases for which the prototype CMs were implemented as a service (a Pre-Creation use case and an Operational use case) are also discussed in this paper.

Modelling and optimisation of a product recovery network

An appropriate logistics network is an important element of the infrastructure of any product recovery company. Small and medium enterprises (SMEs) constitute a major fraction of the product recovery industry with a different business objective and scale of operation from those of original equipment manufacturers. This paper addresses the network design issues for SMEs involved in product recovery activities. A mathematical formulation is presented in an SME context and a subsequent simulation model is developed. A genetic algorithm approach is presented for optimising the network for a single product scenario.

Synchronisation issue of supply chains: a six-sigma constrained random search approach

Supply Chains (SC) can be viewed as a network of facilities or companies in which an order will flow through various business processes and ultimately reach the customer on time. In such networks, end-to-end material and information flows are optimally and collaboratively managed to create value for the customer and other stakeholders. The delivery performance of such networks can be optimised by pushing the workflow through the system in a way that there is a high probability of final products reaching the end user in specified delivery window. This paper addresses the problem of synchronisation of the business processes in a supply chain with the objective of minimising the total cost involved. A mathematical formulation of the problem is developed to relate the costs involved and the tolerances gained. A Genetic Algorithm (GA)-based heuristic is proposed to achieve the near optimal solution of the problem.

Application of Collaboration Moderator Service in Pharmaceutical Industry: A Collaborative Drug Discovery Use Case

Knowledge intensive industries benefit immensely from collaborative projects in virtual organisations. However the complexities of the business processes increase with the interdependencies. Successful operations of virtual organisations depends heavily on knowledge sharing among the partners as this is essential for improving the quality of decisions taken by the participating members. Collaboration moderators are specialist applications designed to address issues related to knowledge sharing and to provide functionality to raise awareness. This paper describes such a collaboration moderator service to aid collaborative drug discovery in a pharmaceutical virtual organisation.

Learning Collaboration Moderator Services: Supporting Knowledge Based Collaboration

Collaboration Moderator Services (CMS) as an evolution of earlier Moderator research has emerged to address the issues relating to knowledge based collaboration by providing a set of functionalities such as raising awareness of business opportunities, problems areas, conflicts, change in the item of interests and lessons learned from collaboration. This paper presents a framework for learning CMS within the context of SYNERGY project. It has been shown that knowledge miners of CMS can be used to learn from the databases of the collaborative networked organizations (CNO) and semi-automatically update the CMS Knowledge Base. A case study from construction project has been used to show that the knowledge miner of CMS can “learn” by extracting various kinds of knowledge from Post Project Reports (PPRs) using different text mining techniques. The discovered knowledge in the form of rules relates to improving the processes, identifying recurring problems, good and bad practices, improving customer relationships and enhancing the coordination between members of CNO.

Prioritising Tendering Activities for small to medium-sized enterprises (SMEs)

The tendering process involves high costs, in terms of time and effort and therefore it is not desirable or sustainable to tender for projects unless the chances of winning are good. Small to medium sized companies do not have enough human resources to enable staff to be dedicated to the job of tending and monitoring market opportunities, and hence company officials have to fit in this job around their usual duties. This paper proposes a knowledge discovery and mining approach to assist the tender offer selection process. Knowledge discovery and mining assures identification and matching of the areas of interest and other criteria of selection of the tender offers, while multi-criteria decision making supports the consideration of other relevant factors for selection.