Janet Efstathiou

An information‐theoretic methodology for measuring the operational complexity of supplier‐customer systems

In a dynamic environment such as the supply chain, even basic supplier‐customer systems with structurally simple information and material flow formations have a tendency to exhibit operational complexity. The operational complexity of supplier‐customer systems is primarily characterised by the uncertainty of the system. As the operational complexity of a system increases there is an associated increase in the amount of information required to monitor and manage that system. Based on this understanding, a novel information‐theoretic entropy‐based methodology for measuring and analysing the operational complexity of supplier‐customer systems has been developed. This paper makes contributions in the theoretical, conceptual and practical developments of the methodology. The methodology can quantitatively detect and prioritise operational complexity hotspots. At the interface, the framework can identify and quantify the transfer of operational complexity. Within the internal manufacturing system, the framework...

Advances on measuring the operational complexity of supplier–customer systems

Even structurally simple supplier–customer systems can be operationally complex. This operational complexity can be colloquially defined as the uncertainty associated with managing the dynamic variations, in time or quantity, across information and material flows at the supplier–customer interface. This paper proposes a means of measuring the information demands placed on supplier–customer systems, as a result of this uncertainty. This paper mathematically models the operational complexity of supplier–customer systems from an information-theoretic perspective. A unique feature of this measure is that it captures, in relative terms, the expected amount of information required to describe the state of the system. The measure provides flexibility in the scope and detail of analysis, while at the same time allowing a systematic hierarchical approach. The application of the measure allows valuable insights to be obtained in terms of the degree of uncertainty, level of control and the detail of monitoring required to manage the operational complexity of supplier–customer systems.

How does Europe Make Its Mind Up? Connections, cliques, and compatibility between countries in the Eurovision Song Contest

We investigate the complex relationships between countries in the Eurovision Song Contest, by recasting past voting data from 1992–2003 in terms of a dynamical network. Our analysis shows that the UK is remarkably compatible, or ‘in tune’, with other European countries during the period of study. Equally surprising is our finding that some other core countries, most notably France, are significantly ‘out of tune’ with the rest of Europe during the same period. In addition, our analysis enables us to confirm a widely-held belief that there are unofficial cliques of countries; however, these cliques are not always the expected ones, nor can their existence be explained solely on the grounds of geographical proximity. The complexity in this system emerges via the group ‘self-assessment’ process, and in the absence of any central controller. One might therefore speculate that such complexity is representative of many real-world situations in which groups of ‘agents’ establish their own inter-relationships and hence ultimately decide their own fate. Possible examples include groups of individuals, societies, political groups or even governments.

A web-based expert system to assess the complexity of manufacturing organizations

Abstract Information-theoretic modelling of manufacturing organizations and their supply chains has led to the development of measures of manufacturing complexity. The measures include assessment of the structural, dynamic and decision-making complexity associated with the processing and movement of material and information around a manufacturing system. A computer program has been written to calculate the decision-making complexity of a manufacturing system, under different system layouts and operating characteristics. In order to make the results of this program accessible to manufacturing organizations, an expert system has been developed to act as a mediator between the program and interested organizations. Given some simple quantitative data on manufacturing performance, the expert system can estimate the organizations complexity and suggest some recommendations to reduce it, based on the data provided by the organization. The expert system will be implemented on the web to enable on-line acquisition and searching of data on companies. The quid pro quo of the expert system is that anonymized data on the organizations will be retained so that complexity benchmarks may be established.

Comparing the impact of different rescheduling strategies on the entropic-related complexity of manufacturing systems

The primary objective of this paper is to compare five rescheduling strategies according to their effectiveness in reducing entropic-related complexity arising from machine breakdowns in manufacturing systems. Entropic-related complexity is the expected amount of information required to describe the state of the system. Previous case studies carried out by the authors have guided computer simulations, which were carried out in Arena 5.0 in combination with MS Excel. Simulation performance is measured by: (1) entropic-related complexity measures, which quantify: (a) the complexity associated with the information content of schedules, and (b) the complexity associated with the variations between schedules; and (2) mean flow time. The results highlight two main points: (a) the importance of reducing unbalanced machine workloads by using the least utilised machine to process the jobs affected by machine breakdowns, and (b) low disruption strategies are effective at reducing entropic-related complexity; this means that applying rescheduling strategies in order to manage complexity can be beneficial up to a point, which, in low disruption strategies, is included in their threshold conditions. The contribution of this paper is two-fold. First, it extends the application of entropic-related complexity to every schedule generated through rescheduling, whereas previous work only applied it to the original schedule. Second, recommendations are proposed to schedulers for improving their rescheduling practice in the face of machine breakdowns. Those recommendations vary according to the manufacturing organisations’ product type and scheduling objectives. Further work includes: (a) preparing a detailed workbook to measure entropic-related complexity at shop-floor level; and (b) extending the analysis to other types of disturbances, such as customer changes.

The complexity of mass customization systems under different inventory strategies

We present a methodology for calculating the information-theoretic complexity of a mass customization (MC) manufacturing system, under various inventory management strategies, and identify the parameters of the whole system that are likely to be the most significant in determining overall system complexity. We apply the methods of the information-theoretic complexity calculation, which provides a generic method for objectively comparing different kinds of system. We present a model of the structure of a mass customizing system, as composed of a push line and a pull line, decoupled by inventory of semi-finished variants. We calculate the information-theoretic complexity of the entire system, and show that the inventory is the main source of complexity in a mass customizing system. We then focus on the impact of different strategies for managing the inventory as methods to reduce complexity. We point out the factors that affect inventory complexity most significantly are the number of stock locations and the number of variants that may be stored there, although the number of stock locations is the more significant of the two. These results can guide the designers and managers of mass customization systems on the system structures that are most likely to have less management overhead, because of the reduced amount of information that is required to know the state of the system.

A research framework for Web-based open decision support systems

With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). In this paper, we propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS and creates a uniform research framework for various decision support systems. The conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also analyze the basic functions and develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS function efficiently. Finally, an illustrative example is studied to support the proposed ideas.

Identifying the underlying structure and dynamic interactions in a voting network

We analyse the structure and behaviour of a specific voting network using a dynamic structure-based methodology which draws on Q-Analysis and social network theory. Our empirical focus is on the Eurovision Song Contest over a period of 20 years. For a multicultural contest of this kind, one of the key questions is how the quality of a song is judged and how voting groups emerge. We investigate structures that may identify the winner based purely on the topology of the network. This provides a basic framework to identify what the characteristics associated with becoming a winner are, and may help to establish a homogenous criterion for subjective measures such as quality. Further, we measure the importance of voting cliques, and present a dynamic model based on a changing multidimensional measure of connectivity in order to reveal the formation of emerging community structure within the contest. Finally, we study the dynamic behaviour exhibited by the network in order to understand the clustering of voting preferences and the relationship between local and global properties.

Application of a simple method of cell design accounting for product demand and operation sequence

Manufacturing facilities may simplify their operations by converting from a process‐based layout to manufacturing cells. Mathematically, many possible configurations of cells exist, so it may prove computationally infeasible to analyse them all. Also, some current methods of cell design do not take account of the pattern of demand of the existing products or the sequence of the operations that are performed on the products. Presents a simple method of designing manufacturing cells, which uses product demand and operations sequence to design feasible cells, while remaining computationally simple. The method uses a standard spreadsheet tool, so is accessible to a wide range of manufacturing facilities. The method is illustrated with an actual application to a press shop manufacturing over 200 products on 20 presses.

Dealing with Uncertainty in Manufacturing: The Impact on Scheduling

Today’s manufacturing environment is characterised by ever shorter product life cycles, greater product variety and quicker response to customers’ demands. To satisfy these requirements, manufacturers introduce greater flexibility to their process, which may lead to higher levels of complexity and uncertainty. Planning and scheduling are affected by these factors. A rigid plan is no longer valid to satisfy all the constraints and changes in the production. Our research, carried out in a leading UK manufacturer, has provided us with an understanding of the realities of the shop-floor and the effects that uncertainty has over the scheduling function. Our work has revealed the need of a new approach for solving the scheduling problem. This perception of scheduling will have to take into account not only the manufacturing variables but also external elements such as organisational features, human factors and information flow.