Ann-Kristin Cordes

Conceptual approach for integrating condition monitoring information and spare parts forecasting methods

Precise estimation of part failures, and hence system breakdowns, is required to reduce or avoid the downtimes of machines and stock-outs. If detected sufficiently early, potentially broken parts of a machine may even lead to not necessarily having to store the respective spare part. For estimating the spare parts demand as accurately as possible, this article conceptualizes an approach for integrating condition monitoring information provided by Intelligent Maintenance Systems and forecasting methods. This concept is validated based on an example evaluation. Thus, the research objective is to improve the forecasting quality of estimated machine breakdowns in order to enhance the planning of the spare parts supply chain.

Conceptual approach for integrating tactical spare parts inventory management and transport planning

The most striking challenges of spare parts supply chain management can be seen in the availability of the needed spare part(s), the ability to deploy the appropriately qualified service personnel, and the provision of required equipment, at the right place and the requested time. To meet these requirements, a well-organized planning of all tasks in spare parts supply chain management is required. The tasks to be considered here are production, inventory, and transport planning, as well as the planning of the service personnel and equipment. Focusing on the two most important planning tasks, being inventory and transportation planning, it is needed to determine the stock levels of all warehouses along a spare parts supply chain and the transports. To satisfy the spare parts demand quickly, sufficient spare parts need to be available while on the other hand the inventory costs shall be reduced. For dealing with this trade-off the inventories as well as the transports have to be aligned along a spare parts supply chain in a simultaneously manner. To address this, this article is providing a conceptual approach how spare parts inventory and transport planning can be integrated. The integration is based on existing methods which are analyzed concerning their applicability to spare parts supply chain management and in how far these methods needs to be extended. Based on this investigation, the result is a conceptual approach of a tactical integrated planning model which is able to align the inventories and transports along a spare parts supply chain by reducing the total costs.

Approach for Integrating Condition Monitoring Information and Forecasting Methods to Enhance Spare Parts Supply Chain Planning

Precise estimation of part failure and hence system breakdowns are required to reduce or avoid the downtimes of machines and inventories. If detected sufficiently early, potentially broken parts of a machine might even lead to no necessity of storing the respective spare part. For estimating the breakdown date as accurately as possible this article conceptualizes an approach for integrating condition monitoring information provided by Intelligent Maintenance Systems and forecasting methods. Thus, the research objective is to improve the forecasting quality of estimated machine breakdowns in order to enhance the planning of the spare parts supply chain.

Simulation model concept for evaluating spare parts supply chain planning methods

Planning the multitude of spare parts supply chains activities, characterized by intermittent demand combined with multi-echelon inventories involves considering highly stochastic processes. Thus, planning results do not achieve the same preciseness as of regular products supply chains. Recent research argues that referred preciseness can be enhanced by using improved demand forecasts which incorporate condition monitoring information. This work conceptualizes a simulation model for evaluating different spare parts planning methods, thus validating if improved forecasting may enhance planning quality. Simulation provides the capability of comparing different scenarios which allow for the aimed validation. The findings are substantiated through a real-world case.

Development of a Reference Model for Spare Parts Logistics

Spare parts logistics deal with several challenges by provisioning the spare part to the end customer due to the sporadic characteristics of the demand. Thereby, the processes and information flows of several spare parts supply chain actors have to be coordinated. To provide a common understanding of all relevant processes and information flows in a spare parts supply chain we develop a reference model for spare parts logistics and identify the central elements. The processes and information flows described in this article cover the initiation of an order to the provisioning of a spare part. After the development, the reference model can form the basis for business process reengineering and investigation of the IT-support for spare parts logistics.

Towards Intelligent Maintenance Systems: Rescuing Human Operator and Context Factors

Abstract Current technologies have used embedded devices for degradation monitoring based on Condition-Based Maintenance (CBM) paradigm for critical parts of equipments. Intelligent Maintenance Systems (IMS) have been proposed in order to autonomously provide failure predictions through data acquisition from sensors. This paper intends to discuss how to capture the operator skill and environment conditions into the IMS. We have adapted the data flow in CBM classical architecture in order to consider the resultant information from maintenance operations associated with the technical teams and their contexts. For this purpose was used a Cyber-Physical Systems (CPS) approach to consider human and context factors. Considering the CPS as system that combines and coordinates physical and computational elements, the CPS incorporates the ability to act in the physical world with the intelligence from cyber or virtual world. In this paper, we propose to use a CPS for taking account human/context factors applied maintenance strategies. The proposed tool, called Toogle-IMS, aims at developing an advanced Human-Computer Interaction (HCI) applied to Intelligent Maintenance System (IMS). We have applied the Toogle-IMS in two case studies associated with: i. mobile robots in maintenance and ii. mobile trucks in shipyards.

A communication procedure between tactical and operational levels in spare parts supply chains

Supply Chain Management has been an important issue for competitiveness in today’s market. Different decision-support models focus on specific time horizons and goals. The most common way of structuring supply chain planning process is dividing it in three different levels: operational, tactical and strategic. However, the planning on one level generally does not communicate with the others, limiting its efficiency and feasibility. The present work proposes a communication procedure between tactical and operation support-decision models in order to coordinate both, thus improving their overall performance. The procedure will be applied to a test case comprising a Spare Parts Supply Chain (SPSC) problem for maintenance in production facilities with the concept of integrating spare parts supply chain and intelligent maintenance systems implemented.

Analyzing and processing intelligent maintenance systems data to use for planning spare parts supply chains

An Intelligent Maintenance System (IMS) provides data about the status of technical devices. Based on sensorial input, IMS analyzes the data and forecasts failures of these devices. The forecasted failures can be used to improve the spare parts demand forecast results as the gathered condition monitoring information provides a more accurate prognosis about the status of the technical devices. The enhanced demand forecasts in the next step build the foundation for planning the activities like inventory, transport, and maintenance management planning along a spare parts supply chain more adequately. To use the data provided by an IMS for forecasting the spare parts demand, the IMS data has to be analyzed and processed as the current existing IMS does not generate condition monitoring information in the data type, which is needed for enhancing the spare parts demand forecast. For that reason, this paper proposes how the IMS can be adapted for generating the needed data type. This is done by developing an IMS simulator based on the same IMS architecture used in the field. An IMS simulator is developed as in real scenarios restrictions are existing concerning the data collection by the installed IMS in the field.

Open Issues for Interfaces on Spare Parts Supply Chain Systems: A Content Generation Methodology

This paper proposes a methodology for content generation to visualization interfaces applied spare parts supply chain systems. Case studies in the context of transportation planning for oil and gas industry will be investigated in order to validate the methodology and to analyze the results. The goal is to provide a methodology to manage and integrate the information from different systems in order to present effective data in visualization interfaces of supply chain systems.