Toni Ahonen

Maintenance communities – a new model for the networked delivery of maintenance services

Emerging industrial service process development combined with managing complexity in service supply networks is an area where literature is still scarce. This paper seeks to critically analyse traditional maintenance business practices and to present a model to support the new production paradigm based on collaborative, value-adding networks. This paper is based on interviews and structured discussions with experts in different fields, and analysis of the results of industrial case studies. Our constructive research approach includes formulation of an advanced model to support a collaborative and networked maintenance business based on the identification of the current key challenges. Value networks are still lacking methods, models and practical business scenarios that support the collaborative provision of maintenance services. Adoption of the model presented in this paper is assumed to support service suppliers in coping with the challenges in dynamic maintenance service supply networks. The originality of our work lies in providing an integrated depiction of our model from several perspectives.

Towards availability and sustainability in customer value assessment of asset management services

Purchasing a solution is an asset management option for a customer of industrial maintenance solution providers. It needs to be justified, e.g. by achieving energy savings or increasing the availability of a production system. Therefore, the value elements of such solutions should be identified and quantified wherever possible. Although research on customer value in product, service and solution management has clearly increased in recent years, a common understanding of comprehensive value assessment in industrial service management is as yet incomplete. In our paper, we present an integrated methodology for assessing the value of asset management services. The approach combines a qualitative service-oriented Quality Function Deployment (QFD) method with a quantitative method for assessing the customer value including availability and economic sustainability elements. The utilisation of the approach is illustrated by means of a real-world case study of a value-based assessment and development of the service portfolio of an industrial solution provider.

Decision Making Situations Define Data Requirements in Fleet Asset Management

Large amounts of data are increasingly gathered in order to support decision making processes in asset management. The challenge is how best to utilise the large amounts of fragmented and unorganised data sets to benefit decision making, also at fleet level. It is therefore important to be able to utilize and combine all the relevant data, both technical and economic, to create new business knowledge to support effective decision making especially within diverse situations. It is also important to acknowledge that different types of data are required in different decision making context. A review of the literature has shown that decision making situations are usually categorized according to the decision making levels, namely strategic, tactical and operational. In addition, they can be classified according to the amount of time used in decision making. For example, two situations can be compared: (1) optimization decision where a large amount of time and consideration is used to determine an optimum solution, and (2) decisions that need to be made instantly. Fleet management of industrial assets suffers from a lack of asset management strategies in order to ensure the correct data is collected, analysed and used to inform critical business decisions with regard to fleet management. In this paper we categorize the decision making process within certain situation and propose a new framework to identify fleet decision making situations.

Asset Management Decisions—Based on System Thinking and Data Analysis

Asset related data is collected in several information systems (e.g. enterprise resource management (ERP) and computerized maintenance management systems (CMMS) systems) at industrial plants. Information systems including asset related data are typically used for operational level decisions (e.g. creating maintenance work orders) but maintenance history data is also valuable when making asset management level decisions (e.g. investment decisions). Even though there is a huge amount of stored data, tacit knowledge is needed for risk conscious asset decisions both for supplementing the data contained in IT-systems and for creating the understanding of the production system itself and its interrelationships. The paper describes how data collected from ERP and CMMS system can be utilized when improving operational efficiency and researching investment opportunities and evaluating investment options.

Assessing the subjective added value of value nets: Which network strategies are really win-win?

As manufacturing companies increasingly focus on their core business, the interest in the utilisation of external services provided by system suppliers and service companies increases. Currently an increasing number of services are purchased from service supply networks. Furthermore, globalisation, complexity of technological innovations and demand for integrated solutions also create need for networking and collaboration. Establishing or improving the performance of the networked service providers, the value net, is a long-term effort, requiring the build up of trust between the partners. The necessary condition of moving from a subcontractor relationship to a strategic network or partnership is the sharing of the view of joint gains in a prospective value net. How do we then evaluate the added value of moving to a new partnership? What network strategies provide the win-win network solution? This paper is a tentative effort in answering these questions based on Decision Analysis.

Tapping the Value Potential of Extended Asset Services – Experiences from Finnish Companies

Abstract Recent developments in information technology and business models enable a wide variety of new services for companies looking for growth in services. Currently, manufacturing companies have been actively developing and providing novel asset based services such as condition monitoring and remote control. However, there is still untapped potential in extending the service delivery to the long-term co-operative development of physical assets over the whole lifecycle. Close collaboration with the end-customer and other stakeholders is needed in order to understand the value generation options. In this paper, we assess some of the asset services manufacturing companies are currently developing. The descriptions of the asset services are based on the results of an industrial workshop in which the companies presented their service development plans. The service propositions are compared with the Total Cost of Ownership and the closed loop life cycle frameworks. Based on the comparison, gaps that indicate potential for extended asset service concepts are recognised. In conclusion, we argue that the manufacturing companies do not recognise the whole potential for asset based services and for optimizing the performance of the end customers′ processes.

Development of Industrial Internet-Related Asset Management Services with Customers

An increasing number of product and service providers aim to gain a competitive advantage through new services enabled by the Industrial Internet. In order to develop and successfully provide Industrial Internet-related services, a company needs to build up related capabilities and construct a strong value proposition in line with real customer needs. This customer and service perspective of the Industrial Internet has so far been rather little studied. Supporting conceptual tools are required. The development of the services relies on how well customers’ business and production environments and management of assets are understood, and therefore this paper proposes a framework that creates necessary new knowledge for the development of new Industrial Internet-related services.

Collaborative development of Maintenance investment management: A case study in pulp and paper industry

The interest in purchasing external maintenance services increases as a strategic choice, as manufacturing companies increasingly focus on their core business. In the case presented in this paper, an external service provider has taken the responsibility of the maintenance functions as a strategic partner. A development project was started to support the creation of profound and functional partnership. Focus of the project was to support the practical collaboration between the partners. The development focused on two activities, in which the both organisations clearly have important roles. These two activities are: management of maintenance investments and operator involvement in maintenance activities. The idea was to improve the collaboration practices by practical collaborative development of these two key activities. Maintenance investment decision making requires functional collaboration between the organisations. The maintenance organisation is responsible for making investment proposals and production organisation makes the final decisions. Originally not much collaboration was planned in this process. Furthermore there was a demand for improving and clarifying the reasoning for proposals. To meet this demand, a working group comprising representatives of both organisations and researchers developed proper commonly agreed criteria, a tool and a process for preparation of maintenance investment proposals. In the developed investment process, the collaboration aspect was taken into account. In this paper, we present the collaborative development process, resulting maintenance investment management development and key findings regarding the importance of practical development efforts done together in building trust and collaboration in a business partnership.

In Search Of Best Practices In Industrial Maintenance: Some Underlying Factors

Abstract Business requirements and characteristics of production systems determine the effective modes of operations in industrial maintenance. In order to identify the best practices the first task is to identify the best performance in various business environments using relevant key performance indicators. The next step is to identify the modes of operations which create the best performance. There are several research strategies to find out the best practices. However, there are a lot of challenges in data collection and therefore a research process requires a long term roadmap in order to boost knowledge on behavior behind peak performance. This paper presents some of the results of a long research process, which form a solid basis for determining the best practices in the area of industrial maintenance.