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Institute
Assessment of IS Integration Efforts to Implement the Internet of Production Reference Architecture
(2018)
As part of a collaborative network, manufacturing companies are required to be agile and accelerate their decision making. To do so, a high amount of data is available and needs to be utilized. To enable this from a company internal information system perspective, the Internet of Production (IoP) describes a future information system (IS) architecture. Core element of the IoP is a digital platform building the basis for a network of cognitive systems. To implement and continuously further develop the IoP, manufacturing companies need to make architecture-related decisions concerning the accessibility of data, the processing of the data as well as the visualization of the information. The goal of this research is the development of a decision-support methodology to make those decisions, taking under consideration the evaluated IS integration effort. Therefore, this paper describes the allocation of IS functions and identifies the effort drivers for the respective IS integration by analyzing the integration possibilities. Conclusively this approach will be validated in a case study.
Generation of a Data Model For Quotation Costing Of Make To Order Manufacturers From Case Studies
(2022)
For contract or make to order manufacturers, quotation costing is a complex process that is mainly performed based on experience. Due to the high diversity of the product range of these mostly small or medium-sized companies (SMEs) and the poor data situation at the time of quotation preparation, the quality of the calculation is subject to strong variations and uncertainties. The gap between the initial quotation costing and the actual costs to be spent (pre- and post-calculation) is crucial to the existence of SMEs. Digitalization in general can help companies to get a better understanding of processes and to generate data. For improving these processes, an understanding of the important data for that specific process is crucial. Accurate quotation costing for customized products is time-consuming and resource-intensive, as there is a lack of an overview of data to be used within the process. This paper therefore derives a data model for supporting quotation costing in the company, based on literature-based costing procedures and recorded case studies for quotation and calculation. Based on the results, SMEs will have a first overview of the needed data for quotation costing to optimize their calculation process.
Methods of machine learning (ML) are notoriously difficult for enterprises to employ productively. Data science is not a core skill of most companies, and acquiring external talent is expensive. Automated machine learning (Auto-ML) aims to alleviate this, democratising machine learning by introducing elements such as low-code / no-code functionalities into its model creation process. Multiple applications are possible for Auto-ML, such as Natural Language Processing (NLP), predictive modelling and optimization. However, employing Auto-ML still proves difficult for companies due to the dynamic vendor market: The solutions vary in scope and functionality while providers do little to delineate their offerings from related solutions like industrial IoT-Platforms. Additionally, the current research on Auto-ML focuses on mathematical optimization of the underlying algorithms, with diminishing returns for end users. The aim of this paper is to provide an overview over available, user-friendly ML technology through a descriptive model of the functions of current Auto-ML solutions. The model was created based on case studies of available solutions and an analysis of relevant literature. This method yielded a comprehensive function tree for Auto-ML solutions along with a methodology to update the descriptive model in case the dynamic provider market changes. Thus, the paper catalyses the use of ML in companies by providing companies and stakeholders with a framework to assess the functional scope of Auto-ML solutions.
Increasing productivity in product-service systems is a vital success factor for industrialized economies and individual businesses. The service production is typically described as an integrated value chain setting, in which the provider and the customer are co-creators.
This paper embraces a characteristic curve model in order to illustrate the influence of the customer on the productivity of service production. The characteristic curves are derived from a system dynamics simulation model for a synchronized takt-based service production. In conclusion this research leads to designs recommendations for service production systems in order to reduce lead times and increase adherence to delivery dates.
Applying Game Theory in Procurement. An Approach for Coping with Dynamic Conditions in Supply Chains
(2014)
Producing companies are facing continually changing conditions accompanied by higher requirements with respect to the flexible configuration of their supply chain. The challenge resulting from this initial situation is to develop systems that have the availability of adjusting their planning procedures and aims depended on the situation and therefore accommodate the increasing demand for flexibility. To address this challenge game theory seems to be a new and promising approach. The aim and added-value of the research work described here is to develop a decision model for the area of procurement using solutions concepts of game theory. Especially in times of high volatility such a decision model can support material requirements planners better than today's common selective planning logics.
In this paper the model to be solved by game theoretic solution concepts is presented. A research study has been conducted which proved the need for combining existing methods of procurement quantity calculation by means of game theoretic solution concepts. Some of the results of this study are presented in this paper. In the last part of the paper a structure for classifying game theoretic models is presented. This structure should support in selecting the appropriate solution concept for real-life decision-situations and is able to support in any practical application-field finding out the most appropriate game theoretic solution concept.
The growth of installed wind capacities generated a market with a huge variety of service offers for operation & maintenance of wind turbines. Different parties like manufacturers, component suppliers as well as independent service providers compete for the attractive after sales market. An innovative service offer which seems to meet the customers’ requirements is the guarantee of availability for wind turbines. However, these service providers are facing new challenges regarding their performance potentials and their financial risks occurring from possible penalties. Service providers have to reconsider their preparedness of performance, their new occurring financials risks, their cooperation and qualification level as well as their localization of service bases. To be able to quantify these new challenges and risks a simulation model has been designed in the context of a German research project named “WinServ”.
A company can choose between three generic competitive strategies. Alongside the strategy of cost leadership are the strategy of differentiation and the strategy of focussing on niches, although we will not be discussing this latter any further here. The strategy of cost leadership is based on the achievement of “economies of scale”, so generating advantage from the benefits of cost reduction, learning curve effects and automation. In the strategy of differentiation the focus is on “economies of scope” which enable the customer-specific products to be offered, but this is generally achieved only with an increase in the complexity of products and processes. In the past it was assumed that these two strategies were mutually exclusive, as an increase in the economies of scale basically leads to a reduction in the economies of scope, and vice versa. But in order to survive in the international competitive arena companies in the high-wage countries need increasingly to offer individually tailored products at competitive prices. The target to be aimed at is therefore customer-specific products at the cost of mass production, so resolving the dilemma between economies of scale and economies of scope. For this it is necessary to optimise the alignment of all the structural elements in both the product and its production, because of the high level of their interdependence.
The areas on which we will focus our review and designs in the following will be what are known as product-production systems, or more briefly, production systems. This topic includes not only the resources and processes of the value creation systems, but also the products produced and offered on the market by a company as one connected entity. In order to tackle the challenges mentioned above, it is necessary to make it possible to measure and compare the current position of any given production system on the see-saw between economies of scale and economies of scope, and then be able to redesign specific facets of them as a second phase. A method of integrative evaluation and design of production systems is presented below for this purpose.
Industrial production in high-wage countries like Germany is still at risk. Yet, there are many counter-examples in which producing companies dominate their competitors by not only compensating for their specific disadvantages in terms of factor costs (e.g. wages, energy, duties and taxes) but rather by minimising waste using synchronising integrativity as well as by obtaining superior adaptivity on alternating conditions. In order to respond to the issue of economic sustainability of industrial production in high-wage countries, the leading production engineering and material research scientists of RWTH Aachen University together with renowned companies have established the Cluster of Excellence “Integrative Production Technology for High-Wage Countries”. This compendium comprises the cluster’s scientific results as well as a selection of business and technology cases, in which these results have been successfully implemented into industrial practice in close cooperation with more than 30 companies of the industrial production sector.
Maximising economies of scale in individualised production is a vital issue for producing companies in high wage countries. A decisive enabler for this is the management of product and process complexity by systematic standardisation. Due to the strong and far-reaching impact of complexity on the value added chain, its management requires an integrative consideration of the entire product and production system.
The following paper introduces a methodology facing this challenge. The core element of this methodology is an integrative and complexity-focused assessment model. This assessment model has been validated experimentally by analysing key company data from more than 50 German toolmaking firms. Findings of this empirical investigation are presented in this paper.
Manufacturing companies of the machinery and equipment industry find themselves more than ever exposed to a rapidly changing competitive environment. In particular, the resulting diversity of planning and control processes confronts organisations and information systems with a significant coordination effort. To this day, planning and execution of order processing – from offer processing to the final shipment of the product – is still a part of the production planning and control (PPC), which is almost entirely integrated into information systems. Though, in order to manage dynamic influences on processes within order processing, there can be found a deficiency in the processing of decision-relevant and real-time information. Partly, the reason for this is a missing or incorrect feedback of process relevant data, so that the planning results, gained by the use of information systems, differ to the current process situation.
The concept of Manufacturing Resource Planning (MRP II) still represents the central logic of production planning and control. However, the centralised and push-oriented MRP II planning logic is not able to plan and measure dynamic processes adequately, which, due to diverse disturbances, often occur in production environments. Furthermore, specific weaknesses of MRP II-based systems are the lack of support for order releases, the planning principle based on average values and the successive planning method as well as the use of limited partial models. As a result a successive planning method leads to a dissection of PPC-tasks into smaller work packages and so strides away from a holistic approach and the achievement of an optimal solution. Similarly, a planning, focusing on a general business objective system, using a partial planning approach due to isolated considerations is not possible. Insufficient consideration of the current load horizon and the current capacity utilization, non-existing or delayed feedback on order progress as well as faults and poor availability and transparency of information can be named as further weaknesses of MRP II-based systems.
Remote services are services enabled by information and communication components and therefore do not require the physical presence of a service technician at the service object to provide a task. The impact of remote service on the capital goods industry has been increasingly significant over the recent yeas. Still many companies struggle with developing and implemenling successful business model, for remote service. This leads to a lot of unaccomplished benefits for the customer as well as for the companies themselves. A survey throughout companies in Ihe industrial machine and plant production sector was conducted in order to determine what successful companies do differently from those that cannot efficiently implement remote service business models.
The study presented in this chapter identifies key suceess factors of companies that effectively implemented remote services for their products. In order to identify the successful companies a scale for measuring remote service success was developed. Only by the use of this scale further findings regarding the success factors were possible. Key findings include the fact that successful companies actively market their remotle service to their customers. Generally they try to approach their remote service business from the operating company's perspective.
Growing information systems (IS) often come along with growing IT complexity, because of emerging rag rug landscapes. This development causes rising IT costs and dependencies, which hinder the maintenance and expansion of the IS landscape. This article outlines the current research on published and presented methods to manage the rising IT complexity in a literature review. Because definitions of “IT complexity” vary a lot in literature, this paper also includes a definition of the term. In addition to that, it delivers a presentation of the used research methodology. Subsequently, it presents the findings in literature, highlights the research gap and – based on the literature analysis – presents the steps that need to be taken. A discussion of the results and a summary complete the article.
In this paper, an approach towards energy management 4.0 will be presented. Energy management 4.0 is understood as an encompassing energy data based concept for manufacturing companies acting in an flexible energy grid of the future with the final goal of autonomous self-optimization Controlling, supervising and scheduling production and logistic steps based on a reliable communication infrastructure and real time data in accordance to achieve a maximum of profitability with regard to human factor is executed.
Guided by a four maturity levels of the "acatech Industrie 4.0 Maturity Index" developed by the German National Academy of Science and Engineering (acatech) different use cases are presented according to the steps of visibility, transparency, prognostic capacity and self-optimization. The basic idea of energy management 4.0 is described and an outlook of further steps that are needed to be evaluated for an implementation are presented.
Growing information systems (IS) often come along with growing IT complexity, because of emerging rag rug landscapes. This development causes rising IT costs and dependencies, which hinder the maintenance and expansion of the IS landscape. This article outlines the current research on published and presented methods to manage the rising IT complexity in a literature review. Because definitions of “IT complexity” vary a lot in literature, this paper also includes a definition of the term. In addition to that, it delivers a presentation of the used research methodology. Subsequently, it presents the findings in literature, highlights the research gap and – based on the literature analysis – presents, the steps that need to be taken. A discussion of the results and a summary complete the article.
Nowadays one of the most challenging tasks of producing companies is the growing complexity due to the globalization and digitalization. Especially in high wage countries, the ability to deliver fast and to a fixed date gets more and more important. To achieve this logistic target, it is necessary to optimize the Production Planning and Control (hereinafter PPC). This study investigates the effects of a change of the scheduling parameters on a target system. The focused research questions are: How can the effect of a scheduling parametersvariation on the target system of the PPC can be displayed efficiently? Is it possible to review the effect of the scheduling parameters-variation quantitatively and to derive action options?
The topics Internet of Things and Industry 4.0 increasingly lead to the fact that the customer is increasingly focused on manufacturing companies. He wants to know delivery date of the product, wants to make changes at short notice, get an individualized product and much more. Technologically, these requirements have already been met, but the structures within the company as well as the operational processes are not yet or only partially prepared to cope with the increasing complexity and dynamics of production. This leads to many deviations with which the production controller must deal, whether they are complex or trivial.
In order to counteract the increasing number and frequency of deviation situations which are currently encountered with complex manual interventions, it is necessary to systematically evaluate deviations and then to allocate them a dominant reaction strategy (manual, partially automated, automated) from which a suitable reaction measure can be derived. This relieves the production controller, since assistance systems partially eliminate deviations independently.
As a result, the production controller gets more time to deal with the cause of deviations so that a new occurrence of deviations can be avoided and the number of deviations can be reduced sustainably. The following paper provides a solution for the assessment of deviations. In addition, it includes differentiation logic to allocate one of the three different reaction strategies to the identified deviation.
Production in high-wage countries can be made more efficient, cost-effective, and flexible by solving the conflict between planning and value orientation. A promising approach is to focus on planning and decision-making processes (production planning and control, design of production processes and machinery, etc.) and to aim to maximize overall planning efficiency. Planning efficiency can be expressed as the ratio between the benefit generated by preparing detailed process instructions to produce the parts or components and the corresponding planning efforts. Industrial companies wanting to gain a competitive advantage in dynamic global markets have to identify a set of non-dominated solutions with the most favorable effort–benefit ratio rather than a single solution. The optimum between detailed planning and the immediate implementation of value-adding activities (process steps) in the process chain needs to be found dynamically for each product.
This research area focuses on the management systems and principles of a production system. It aims at controlling the complex interplay of heterogeneous processes in a highly dynamic environment, with special focus on individualized products in high-wage countries. The project addresses the comprehensive application of self-optimizing principles on all levels of the value chain. This implies the integration of self-optimizing control loops on cell level, with those addressing the production planning and control as well as supply chain and quality management aspects. A specific focus is on the consideration of human decisions during the production process. To establish socio-technical control loops, it is necessary to understand how human decisions are made in diffuse working processes as well as how cognitive and affective abilities form the human factor within production processes.
Nowadays, providing purchasable goods is not enough for a company to survive on the global market. Because of competitive prices and a large range of products available, companies need to offer additional benefits to their customers in order to create a unique selling point. They add services to their product portfolio and offer clients the opportunity to acquire an additional service solution to go with it. The offered services need to fit to the customer's needs, resulting in a variety of available services, great complexity of the service range and decreasing transparency of the resource utilization. This paper addresses the problem by identifying variant-creating factors in product service systems, transferring them into an organizational framework and verifying their significance.
This paper contributes to an assessment framework for valuing data as an asset. Particularly industrial manufacturers developing and delivering Smart Product Service Systems (Smart PSS) are comprehensively depended on the business value derived by processing data. However, there is a lack in a framework for capturing and comparing the Smart PSS data value with the purpose of increasing the accountability of data initiatives. Therefore a qualitative data value assessment approach was developed and specified on Smart PSS, based on an industrial case study research. [https://link.springer.com/chapter/10.1007/978-3-030-57997-5_39]