Juha-Matti Lehtonen

The impact of increasing demand visibility on production and inventory control efficiency

Information sharing practices such as vendor‐managed inventory (VMI) give manufacturers access to more accurate demand information, e.g. customer sales data, than before. The value of this type of information sharing has been established in many studies. However, most of the research has focused on the ideal situation of the manufacturer having access to information from all downstream parties. In practice, this is rarely the case. In this paper, discrete‐event simulation is used to examine how a manufacturer can combine traditional order data available from non‐VMI customers with sales data available from VMI customers in its production and inventory control and what impact this has on the manufacturers operational efficiency. The simulation model is based on a real‐life VMI implementation and uses actual demand and product data. The key finding is that even for products with stable demand a partial improvement of demand visibility can improve production and inventory control efficiency, but that the value of visibility greatly depends on the target products’ replenishment frequencies and the production planning cycle employed by the manufacturer.

Modelling in product and supply chain design: literature survey and case study

This paper presents a framework for supply chain decision‐making. The framework is used to gain insights into applications of modelling. Current modelling practice is reviewed through a literature survey. The principal finding is a lack of published research in the area of modelling supply chain effects in the product development phase. However, it is in the product development phase where the majority of product life‐cycle costs are determined. As a guideline for further case research, we propose an approach for integration in product life cycle modelling systems. For practitioners, we point out some major requirements for implementation. Finally, we demonstrate an early application of some of the ideas.

Managing projects front-end: incorporating a strategic early view to project management with simulation

Abstract The article introduces a project management approach, which focuses on adopting a strategic view in the project implementation process. Such strategic view means that a consideration on the purpose of the project as a whole must be maintained in the course of project implementation. This includes adopting and maintaining the focus on the functionality and operability features of the project product. The functionality simulation approach itself is well known, e.g. in system engineering design. This article puts discrete event simulation in place in the project implementation process by suggesting that it can help to introduce new insights to conventional project scope management practices. Four simulation cases are presented to illustrate empirically how the management focus is casted in a strategic way to the functionality and operability of the project product. The cases provide understanding of the use of such simulation approach in the course of the project implementation process. The suggested simulation of the functionality of the project product introduces a directing view to project scope management, and this way it provides directions for operative tools that are designed for putting the component parts of the project together.

Cardiac surgery productivity and throughput improvements

PURPOSE The high variability in cardiac surgery length--is one of the main challenges for staff managing productivity. This study aims to evaluate the impact of six interventions on open-heart surgery operating theatre productivity. DESIGN/METHODOLOGY/APPROACH A discrete operating theatre event simulation model with empirical operation time input data from 2603 patients is used to evaluate the effect that these process interventions have on the surgery output and overtime work. A linear regression model was used to get operation time forecasts for surgery scheduling while it also could be used to explain operation time. FINDINGS A forecasting model based on the linear regression of variables available before the surgery explains 46 per cent operating time variance. The main factors influencing operation length were type of operation, redoing the operation and the head surgeon. Reduction of changeover time between surgeries by inducing anaesthesia outside an operating theatre and by reducing slack time at the end of day after a second surgery have the strongest effects on surgery output and productivity. A more accurate operation time forecast did not have any effect on output, although improved operation time forecast did decrease overtime work. RESEARCH LIMITATIONS/IMPLICATIONS A reduction in the operation time itself is not studied in this article. However, the forecasting model can also be applied to discover which factors are most significant in explaining variation in the length of open-heart surgery. PRACTICAL IMPLICATIONS The challenge in scheduling two open-heart surgeries in one day can be partly resolved by increasing the length of the day, decreasing the time between two surgeries or by improving patient scheduling procedures so that two short surgeries can be paired. ORIGINALITY/VALUE A linear regression model is created in the paper to increase the accuracy of operation time forecasting and to identify factors that have the most influence on operation time. A simulation model is used to analyse the impact of improved surgical length forecasting and five selected process interventions on productivity in cardiac surgery.

Combining optimisation and simulation for steel production scheduling

Purpose – Scheduling problems in steel plants tend to be difficult and require complex algorithms due to many constraints. An approach is presented where only the main constraints are included in the scheduling algorithm. The schedule is validated using a discrete‐event simulation model that includes additional detail.Design/methodology/approach – The combined approach is utilised for production scheduling in a steel mill in Finland. Operational performance of the steel mill is measured before and after software installation. The paper presents the scheduling environment, the software application and the resulting increase of production.Findings – Case experiences indicate that combining optimisation techniques with simulation is beneficial. The optimisation can be kept simpler as validation with a simulation model increases the credibility and accuracy of the resulting schedule. During software development and testing, the simulation model offered a testing environment for the optimisation algorithm.Prac...

Production and supply management strategies in Nordic paper mills

The traditional production management strategy in paper manufacturing is based on a volume-intensive approach. This involves the measurement of overall performance or productivity, while aiming at a high level of capacity utilisation and minimum waste levels. This approach has proved successful in mills producing high volumes with a limited and standardised product range. The situation changes radically when paper and board products are being tailored to customer-specified dimensions and quantities. The volume-based approach is no longer appropriate, and production has to be controlled by an approach that considers inventory performance along the full length of the supply chains. This paper presents five empirical examples to illustrate the use of the two strategies. The detailed analyses of production cycles, the logistical solutions applied and the inventory levels at various stages of the supply chain, show that the Nordic paper industry is slow, with average lead times of 79 days to market. When production cycles are reduced and logistical alternatives are fully exploited, it can be seen that 30% of the inventories can be regarded as slack. The summary of the cases shows that speedier operations easily generate direct cost savings amounting to 2-5% of annual turnover. All these results can be achieved without additional investment; all that is required is a change in production planning principles and logistical control procedures. The paper concludes with a challenge to the Nordic paper industry to be the first in its field to achieve the higher level of productivity that faster operations can generate.

Is just‐in‐time applicable in paper industry logistics?

There is a large body of knowledge on logistics and production control, including just‐in‐time (JIT) logistics. However, the applications specific to paper industry logistics are scarce and somewhat conflicting. Examines the potential contribution of alternative logistics systems in the paper industry and the scope for efficiency gains through the application of JIT logistics systems. Multiple case studies are used, with simulation for alternative business scenarios. The results indicate considerable scope for improvements in paper industry logistics, with many of the benefits deriving from JIT applications.

The effect of demand visibility in product introductions

Purpose – Aims to examine the value of manufacturer access to downstream demand information in managing product introductions and to Identify factors affecting this value.Design/methodology/approach – Simulation based on actual data on 19 product introductions is used for comparing different types of demand information and their usefulness to a manufacturer. Two metrics are introduced. Bias indicates if there is a consistent difference between demand information from two sources. Delay in demand synchronization measures how long it takes for demand information from two sources to start conveying demand similarly in a transient situation.Findings – Finds that, in the supply chain examined, demand variability is mainly induced by distributors, whereas bias and delay in demand synchronization are mainly induced by retail outlets, especially for products with large wholesale packages compared with their sales.Research limitations/implications – The simulation model is simple and does not enable realistic exam...

A methodology for data gathering and analysis in a logistics simulation project

Presents a methodology called controllability analysis in logistics. Controllability focuses on two first steps of the simulation project: problem definition; and data gathering and analysis. The aim of the analysis is to reveal the potential improvement areas, and define and analyse the data so that they are ready for the simulation process. Clarifies with a case study the methodology and its use as a part of a logistics simulation project.

Logistics performance measurement — an application to pulp and paper industry

At present, the most common company level inventory performance yardstick is inventory costs in relationship to revenue. This yardstick does not adequately reflect differences in the scope of vertical integration between different companies. The first objective is to develop a suitable yardstick for inventory performance that could enable strategic or company level screening for the need for improvement. This new yardstick is then tested with pulp and paper industry statistics and annual report data.