This paper presents how a Life cycle cost or Total cost of ownership analysis has been performed on machining equipment in a Swedish company. Life cycle cost models used in case studies are compared to an empirical model, used at the company, where dynamic energy, fluid, and maintenance cost are included. Linear and variable factors in the models are analyzed and discussed regarding data availability and estimation, especially with emphasis on maintenance. The life cycle cost aspect of the equipment give guidelines to consider operation, maintenance, tools, energy, and fluid cost in addition to acquisition cost, when designing/specifying the equipment

In order for factories to stay competitive in the current open global market, there should be efforts to put on optimizing the value stream of producing goods. Within this context, Industrial Internet of Things (IIoT) has been emerged as a technology aiming at achieving high productivity performance in manufacturing. A smart manufacturing approach also requires a smart maintenance management as it plays a crucial role in securing the productivity. IIoT applications are traditionally completed by the cloud computing technology to serve the required services. In this paper, we argue that maintenance processes have requirements that cannot be accomplished by solely the cloud computing technology. We identify several of these requirements. Then, we propose a platform using the fog computing technology, as a recently raised technology in IIoT, to enhance the smart maintenance management. We also discuss the ability of the platform in fulfilling the identified requirements.

This paper presents a guide for implementation of Condition Based Maintenance (CBM) in a manufacturing industry, considering the technical constituents and organizational aspects when implementing CBM. The empirical base for the study is a case study from a major manufacturing site in Sweden. The data was collected during a pilot project to implement CBM at the case company. The purpose of the pilot study at the company was to implement online condition monitoring on some of the critical components in the hardening process. Hereby, two of the main online condition monitoring techniques namely vibration analysis and Shock Pulse Method (SPM) have been implemented and tested on electric motors to monitor bearing conditions. The paper presents the process of implementation and the elements included in this process. Some of the main elements in the implementation process are selection of the components to be monitored, techniques and technologies as well as installation of the technologies and finally how to analyze the results from the condition monitoring. The data from online condition monitoring on the electric motors, driving the furnace fans, are recorded and presented in the paper including breakdown data on two objects. This information is leading to useful and reliable knowledge for maintenance work to be cost effective and be able to increase the overall equipment availability (OEA). In addition to this, the result indicates to what extent advanced CBM practices are applicable in the hardening environment in the manufacturing company and it provides guidance for further research and development in this area. The paper concludes with a discussion on possible future trends and research areas, needed to increase the effective and efficient use of CBM.

This paper presents a proposed guide for analysis of the costs and benefits of implementing Condition Based Maintenance (CBM) in manufacturing industry. The guide will be exemplified with results from a case study performed in a real CBM implementation in hardening and machining processes in a large manufacturing facility. The result indicates factors that ought to be taken into consideration in order to evaluate both the cost of implementing CBM and its benefits. These factors indicate the benefits of CBM mostly by reducing the losses due to damage in the production equipment, including capital loss, production loss, quality loss, environmental loss, safety loss etc. By analyzing the empirical data, the most potential savings by implementing CBM are presented as; reducing the probability of having maximal damage in the production equipment and, reducing production losses particularly in high production volumes.

Purpose: The purpose of this paper is to exemplify and discuss the potential in strategic maintenance development.Design/methodology/approach: This paper is based on a three‐year industrial case study, conducted in three different companies within manufacturing industry.Findings: All three companies have showed substantial improvements in the chosen maintenance related KPIs. Further, the management has increased the insight on maintenance as a contributor to company competitiveness.Research limitations/implications: None of the companies has used any financial KPI for their strategic maintenance development. It would be of future interest to study the concept Cost of Poor Maintenance as an evaluation tool for strategic maintenance development.Practical implications: This study exemplifies the potential of strategic maintenance development in manufacturing industry.Originality/value: This paper shows the results from three years of formulation, implementation, and evaluation of maintenance strategies.