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In this study, the authors explore how novel and relevant technologies can change the overall design of systems, and which factors influence the design of resilient systems in particular. After evaluating the effects of these factors, the authors describe the potential role of AM-supported maintenance operations in military logistics and draw broader conclusions regarding designing for resilience.

The authors build a simulation model of the AM-supported maintenance capability of a mechanised battalion to analyse factors affecting its resilience. AM production capacity specifically refers to metal printing and was verified by data generated from 3D printing of the actual APC parts.

The current AM speed is not able to increase resilience at the depot level, so at present, increasing the spare parts inventory is a better way to improve resilience. However, with future improvements in speed the AM may become feasible in battlefield maintenance.

AM holds great promise in increasing resilience of especially the spare part logistics. At present technology, it is not yet fully realised in the case.

The authors suggest a concrete system performance measure, where reaching a concrete limit, system resilience is lost. The authors present arguments for a definition of resilience where pre-disruption activities are not part of resilience. The authors maintain that simulation, with its ability to include detail, is well-suited in design-for-resilience because supply chains are context dependent and disruptions unexpected.

The purpose of this paper is to propose and test a multi-criteria decision analysis (MCDA) approach based on an additive value function (AVF) to select the most economically advantageous tender under European Union public procurement regulations.

A case study in which the AVF tender evaluation model is constructed by the procurement personnel and the results of the original, real-life public procurement evaluation model are compared to those discovered by the MCDA approach.

The AVF model captures the preferences of the procurement authority in a more reliable and transparent manner than commonly used evaluation models based on scoring formulas.

While commonly used in public procurement, relative scoring formulas can neither present the preferences of a procurement unit accurately nor do they enable bidders to draft bids according to these preferences. The proposed MCDA approach can achieve both.

The contribution of this paper is threefold. First, the successful construction of the AVF model with procurement personnel is introduced. Second, the model is used in an actual, real-life case. Third, a thoughtful comparison of features, structures and results of the AVF model and the evaluation model using scoring formulas is presented.

Studies the problem of producing a product range with high customer service in the implosive industries. In the implosive industries a wide range of end products are manufactured from a limited number of standard materials. The problem of producing a product range with high customer service is studied within the framework of product range, capacity and customer acceptable lead time. In the existing just‐in‐time literature, strong emphasis is put on set‐up and through‐put time reduction for achieving high product availability with low cost. However, the decision regarding the product range and its implications on production control is not adequately considered. It is proposed that the relevant time scope to consider demand and capacity is the product range cycle. Three cases from the food and paper industry are studied. The cases indicate constraints for achieving quick response capability.

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.

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.

Previous studies approach surgery scheduling mainly from the mathematical modeling perspective which is often hard to apply in a practical environment. The aim of this study is to develop a practical scheduling system that considers the advantages of both surgery categorization and newsvendor model to surgery scheduling.

The research was carried out in a Finnish orthopaedic specialist centre that performs only joint replacement surgery. Four surgery categorization scenarios were defined and their productivity analyzed by simulation and newsvendor model.

Detailed analyses of surgery durations and the use of more accurate case categories and their combinations in scheduling improved OR productivity 11.3 percent when compared to the base case. Planning to have one OR team to work longer led to remarkable decrease in scheduling inefficiency.

In surgical services, productivity and cost‐efficiency can be improved by utilizing historical data in case scheduling and by increasing flexibility in personnel management.

The study increases the understanding of practical scheduling methods used to improve efficiency in surgical services.

Aims to examine the value of manufacturer access to downstream demand information in managing product introductions and to Identify factors affecting this value.

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.

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.

The simulation model is simple and does not enable realistic examination of how a manufacturer could best use downstream demand data in managing its operations. Further research including such mechanisms as forecasts and stock‐outs is needed.

Provides a means for manufacturers to assess when they should invest in gaining access to downstream demand information and to estimate when their traditional information sources start to accurately convey end‐customer demand for new products.

Although it has been suggested that the value of access to downstream demand information could be greatest in situations with transient or irregular demand, such as product introductions, this claim has not yet been thoroughly examined. This study is a first attempt at filling this gap in the theory.

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.

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.

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.

The case implementation was a success that increased production without making trade‐offs with other production goals. Company management estimate the productivity increase directly caused by the project to be worth €2,500,000 annually.

The paper presents a successful application of simulation for schedule validation in a complex and demanding environment.

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.

A discrete operating theatre event simulation model with empirical operation time input data from 2,603 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.

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.

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.

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.

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.

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 manufacturer's 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.