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The integration of additive manufacturing (AM) processes into a production environment requires a cost‐model that allows the precise estimation of the total cost per part, although the part might be produced in the same build job together with other parts of different sizes, complexities and quantities. Several cost‐models have been proposed in the past, but most of them are not able to calculate the costs for each single part in a mixed build job or are not suitable for Selective Laser Melting (SLM). The purpose of this paper is to develop a cost model, including all pre‐ and post‐processing steps linked to SLM.

Based on collected data and the generic cost model of Alexander et al., an adapted model was developed for the SLM process including all required pre‐ and post‐processes. Each process was analysed and modelled in detail, allowing an evaluation of the influences of the different geometries on the cost of each part.

By simultaneously building up multiple parts, the manufacturing as well as the set‐up time and therefore the total cost per part can be significantly reduced. In the presented case study a cost reduction of 41 per cent can be achieved in average.

Using different cost allocation algorithms, the developed cost model enables a precise determination of total cost per part avoiding that any geometry is preferred in simultaneous manufacture. This helps to optimize build jobs and to manufacture SLM parts more economically by pooling parts from different projects, whereas the cost per part can still be precisely determined.

Describes the introduction of a quality costing system, using the process model, within a division of GEC Alsthom Engineering Systems Ltd. The system was introduced to identify and prioritize improvement areas within the context of a continuous improvement programme. Includes a critical review of a former quality costing system within the division based on the prevention, appraisal and failure model. Initial work focused on the use of the IDEF methodology, recommended in BS 6143: Part 1: 1992, to model major business processes. However, this approach was found to be inappropriate as the models created were complex and failed to gain widespread acceptance within the division. A hybrid model, using integrated flowcharts, was developed; this proved successful in securing understanding and ownership of major processes. Indicates a cost of non‐conformance of approximately 10 per cent and identifies four main areas for improvement activities.

This study presents a framework to estimate throughput and cost of additive manufacturing (AM) as related to process parameters, material thermodynamic properties and machine specifications. Taking a 3D model of the part design as input, the model uses a parametrization of the rate-limiting physics of the AM build process – herein focusing on laser powder bed fusion (LPBF) and scaling of LPBF melt pool geometry – to estimate part- and material-specific build time. From this estimate, per-part cost is calculated using a quantity-dependent activity-based production model.

Analysis tools that assess how design variables and process parameters influence production cost increase our understanding of the economics of AM, thereby supporting its practical adoption. To this aim, our framework produces a representative scaling among process parameters, build rate and production cost.

For exemplary alloys and LPBF system specifications, predictions reveal the underlying tradeoff between production cost and machine capability, and look beyond the capability of currently commercially available equipment. As a proxy for build quality, the number of times each point in the build is re-melted is derived analytically as a function of process parameters, showcasing the tradeoff between print quality due to increased melting cycles, and throughput.

Typical cost models for AM only assess single operating points and are not coupled to models of the representative rate-limiting process physics. The present analysis of LPBF elucidates this important coupling, revealing tradeoffs between equipment capability and production cost, and looking beyond the limits of current commercially available equipment.

The paper provides an overview of research published in the innovation and operations management (IOM) literature on 15 methods for cost management in new product development, and it provides a comparison to an earlier review of the management accounting (MA) literature (Wouters & Morales, 2014).

This structured literature search covers papers published in 23 journals in IOM in the period 1990–2014.

The search yielded a sample of 208 unique papers with 275 results (one paper could refer to multiple cost management methods). The top 3 methods are modular design, component commonality, and product platforms, with 115 results (42%) together. In the MA literature, these three methods accounted for 29%, but target costing was the most researched cost management method by far (26%). Simulation is the most frequently used research method in the IOM literature, whereas this was averagely used in the MA literature; qualitative studies were the most frequently used research method in the MA literature, whereas this was averagely used in the IOM literature. We found a lot of papers presenting practical approaches or decision models as a further development of a particular cost management method, which is a clear difference from the MA literature.

This review focused on the same cost management methods, and future research could also consider other cost management methods which are likely to be more important in the IOM literature compared to the MA literature. Future research could also investigate innovative cost management practices in more detail through longitudinal case studies.

This review of research on methods for cost management published outside the MA literature provides an overview for MA researchers. It highlights key differences between both literatures in their research of the same cost management methods.

The purpose of this paper is to describe research which investigated the interdependencies between facility management performance and costs, and primary processes in hospitals. Through the implementation of the German diagnosis related grouping (DRG) system and the resulting cost pressure, the need for optimized use and operation of the spatial resources in hospitals is growing. In the DRG system, the provision of ready to use infrastructure is treated as a fixed cost and is allocated to patient cases by a single cost driver. In reality, very different services are needed to provide ready to use functional space.

A primary activity based cost model for facility management (FM) services in relation to functional space units in the hospital is developed. Using process and cost data of an empiric research study from four German hospitals, a model is developed for a key functional space unit in the hospital, the operation unit. The relevant FM services structured by a product‐oriented approach are determined by real data. For these services, process figures are derived and implemented in a basic cost estimation model. The cost estimation model is compared to the cost approach of the DRG system.

In an explorative study, the model provides an approach for a patient focused cost allocation of FM services for the operation unit. Depending on the time spectrum of operations great differences between this approach and the legal cost allocation approached in Germany can be determined. One way for hospitals to face the consequences may be the determination and optimization of relevant FM services according to a primary process portfolio.

The activity based cost model should be developed for further space units in the hospital. Thus, a holistic approach to FM and strategic planning of space and FM services could be achieved. Further, the explorative study should be enlarged to a greater database for the development of general key figures for FM in relation to the primary processes.

The model can be used by hospitals for strategic planning of the FM costs and services in relation to the capacity and utilization of the operation unit. The impact of changes of the primary performance portfolio on the utilization of corresponding infrastructure can be simulated. Thus, cost data can be made available to support strategic decisions.

There is no existing cost model for the hospital considering FM in a holistic way in relation to the primary processes.

The purpose of this research is to develop an integrated model for composite rotor blade manufacturing cost estimates at the conceptual design stage. The integrated model seeks to provide a rapid and dynamic feedback based on evaluating the manufacturing cost estimate for a new product design at the conceptual design stage. This paper describes the automated estimating process for design to manufacturing cost of composite rotor blade.

An integrated approach is implemented for evaluating the manufacturing cost estimates. The paper develops each module of the computer‐aided parametric model generation, time estimation models for composite manufacturing processes and decision support system. Finally, process flow data integration is done for all the modules. An example for a complicated geometric rotor blade is shown in this research paper. The results are compared in different design parameters and discussed.

The data integration for this approach was built by using ModelCenter^® software. It is easier and more robust to apply than the other proposed methods. The selection of design, material and manufacturing parameters is achieved by integrated model within a short period of time.

This paper provides an integrated concurrent approach for manufacturing cost evaluation of composite rotor blade. Manufacturing factors could be considered at the early stage of product development phase.

This paper suggests an effective and efficient way of evaluating the manufacturing cost at the conceptual stage of the design process. The concurrent engineering and integrated product process development approaches were addressed.

The purpose of this paper is to propose a service cost model which can be used to evaluate the impact of different management functionalities or network platforms to the service cost.

Following the validation of the importance that OpEx has on the overall TCO, a classification of the costs is proposed, based on their relation to the network. Two main types of costs have been identified: network based costs and service based costs. Both cost types have been modeled as a set of interconnected processes based on the network and service life cycle respectively. Network and service cost models have been integrated into a single framework. These models have been implemented as Markov chains, which include the dynamic behavior of services. Two different methods for the implementation (analytical versus non‐analytical) have been compared from the implementation and computation time point of view. The proposed service model has been used in two case studies: cost comparison of different types of services on different platforms; and impact of the service type distribution on the overall service cost on different platforms.

This paper finds the utility that the proposed cost model has. It has been shown that the impact on the overall service cost that a particular network platform capability such as the possibility of establishing point to multipoint connections has.. The proposed network and service cost models can be used on different types of networks and services.

The paper presents a general service cost model that can be used to study the impact of any management functionality or network platform has on the service cost.

In order for the aerospace industry to achieve success in export markets through the provision of high levels of product choice, it will need to develop and economically use many new materials and manufacturing processes. Examines how the constraints imposed by changing market trends affect the identification of “cost estimating relationships” and investigates their relative benefits and limitations in terms of their effects on the overall cost model development process. A method of establishing cost estimating relationships that appears to offer benefits to the cost modelling process is that of artificial neural networks (ANNs). Using the Taguchi method, a series of experiments have been undertaken to select an appropriate network for the “turning process”. The estimation accuracy and robustness of cost models developed using suitable ANN structures have then been examined under varying conditions in order to identify guidelines.

The purpose of this study is to present a report on the development of an improved mathematical model for quantifying the cost of quality. In addition, a simulation model is developed using real-life industrial data; the model is used to investigate the impact of certain quality control level plans on cost of quality.

The cost of the quality model was developed based on the reported literature and suggestion from the company quality control manager. An extensive discussion was conducted with the quality control supervisors in the company to develop some quality control plans to investigate their impact on cost of quality. A simulation model that represents a specific section of the process at the company was used to carry out the investigation. The results were analysed and compared with some important findings reported in the literature that describe the characteristics of costs of quality.

The simulation work provides valuable insights into the behavior of the different components that constitute the total cost of quality. The results show that reduction of failure costs can be achieved at low or no-subsequent increase in the non-conformance expenditure. In addition, it seems that the traditional accounting system approach may no longer be adequate since it depends mainly on direct labour costs. The results indicate that the direct labour cost is only contributing by about 3 percent of the total cost of quality.

This paper focuses on the development of a comprehensive model for quantifying the cost of quality in a semiconductor company. Future research is needed to expand the model for more complex process configuration. In addition, the developed model could be extended to deal with variant defect rates.

This study presents an advanced theoretical model for cost quality that enhanced models of quality presented in the literature. Using the developed cost of the quality model, a comprehensive simulation was carried out to investigate the impact of some quality plans on cost of quality. The study clearly indicates important evidence to justify the implementation of cost of quality models in real-life industry.

This study aims to take a public goods approach to understand relationships between collecting and contributing knowledge to an online knowledge sharing portal (KSP), mental model processing and outcomes at the individual and collective levels.

This study reports on a survey (N = 602) among tax professionals, examining the perceived individual and collective benefits and costs associated with collecting and contributing knowledge. Hypotheses were tested using structural equation modeling.

Collecting and contributing knowledge led to considerable mental model processing of the knowledge. That in turn significantly influenced (primarily) individual and (some) collective costs and benefits. Results varied by the kinds of knowledge sharing. Whether directly from knowledge sharing, or mediated through mental modeling, the perceived costs and benefits may be internalized as an individual good rather than being interpreted at the collective level as a public good.

The study is situated in the early stages of a wiki-type online KSP. A focus on the learning potential of the system could serve to draw in new users and contributors, heightening perceptions of the public goods dimension of a KSP.

A focus on the learning potential of the system could serve to draw in new users, and thus the number of subsequent contributors, heightening perceptions of the collective, public goods dimension of a KSP.

This study explores how knowledge sharing and mental model processing are directly and indirectly associated with individual and collective costs and benefits. As online knowledge sharing is both an individual and public good, costs and benefits must be considered from both perspectives.