Industry 4.0: The Future of Indo-German Industrial Collaboration

Industry 4.0 can be described as the fourth industrial revolution, a mega- trend that affects every company around the world. It envisions interconnections and collaboration between people, products and machines within and across enterprises. Why does Industry 4.0 make for an excellent platform for industrial collaboration between India and Germany? The answers lie in economic as well as social factors. Both countries have strengths and weakness and strategic collaboration using the principles of Industry 4.0 can help both increase their industrial output, GDP and make optimal use of human resources. As a global heavy weight in manufacturing and machine export, Germany has a leading position in the development and deployment of Industry 4.0 concepts and technology. However, its IT sector, formed by a labor force of 800,000 employees, is not enough. It needs more professionals to reach its full potential. India, on the other hand, is a global leader in IT and business process outsourcing. But its manufacturing industry needs to grow significantly and compete globally. These realities clearly show the need for Industry 4.0-based collaboration between Germany and India. So how does Industry 4.0 work? In a first step, we look at the technical pers- pective – the vertical and horizontal integration of Industry 4.0 principles in enterprises. Vertical integration refers to operations within Smart Factories and horizontal integration to Smart Supply Chains across businesses. In the second step, we look at manufacturing, chemical industry and the IT sector as potential targets for collaboration between the two countries. We use case studies to illustrate the benefits of the deployment of Industry 4.0. Potential collaboration patterns are discussed along different forms of value chains and along companies’ ability to achieve Industry 4.0 status. We analyse the social impact of Industry 4.0 on India and Germany and find that it works very well in the coming years. Germany with its dwindling labor force might be compensated through the automation. This will ensure continued high productivity levels and rise in GDP. India, on the other hand has a burgeoning labor market, with 10 million workers annually entering the job market. Given that the manufacturing sector will be at par with Europe in efficiency and costs by 2023, pressure on India’s labor force will increase even more. Even its robust IT sector will suffer fewer hires because of increased automation. Rapid development of technologies – for the Internet of Things (IoT) or for connectivity like Low-Power WAN – makes skilling and reskilling of the labor force critical for augmenting smart manufacturing. India and Germany have been collaborating at three levels relevant to Industry 4.0 – industry, government and academics. How can these be taken forward? The two countries have a long history of trade. The Indo-German Chamber of Commerce (IGCC) is the largest such chamber in India and the largest German chamber worldwide. VDMA (Verband Deutscher Maschinen- und Anlagenbau, Mechanical Engineering Industry Association), the largest industry association in Europe, maintains offices in India. Indian key players in IT, in turn, have subsidia- ries in Germany and cooperate with German companies in the area of Industry 4.0. Collaboration is also supported on governmental level. As government initiatives go, India has launched the “Make in India” initiative and the “Make in India Mittelstand! (MIIM)” programme as a part of it. The Indian Government is also supporting “smart manufacturing” initiatives in a major way. Centers of Excellence driven by the industry and academic bodies are being set up. Germany and India have a long tradition of research collaboration as well. Germany is the second scientific collaborator of India and Indian students form the third largest group of foreign students in Germany. German institutions like the German Academic Exchange Service (DAAD) or the German House for Research and Innovation (DWIH) are working to strengthen ties between the scientific communities of the two countries, and between their academia and industry. What prevents Industry 4.0 from becoming a more widely used technology? Recent surveys in Germany and India show that awareness about Industry 4.0 is still low, especially among small and medium manufacturing enterprises. IT companies, on the other hand, are better prepared. There is a broad demand for support, regarding customtailored solutions, information on case studies and the willingness to participate in Industry 4.0 pilot projects and to engage in its platform and networking activities. We also found similar responses at workshops conducted with Industry 4.0 stakehold- ers in June 2017 in Bangalore and Pune and in an online survey. What can be done to change this? Both countries should strengthen their efforts to create awareness for Industry 4.0, especially among small and medium enterprises. Germany should also put more emphasis on making their Industry 4.0 technology known to the Indian market. India’s IT giants, on the other hand, should make their Industry 4.0 offers more visible to the German market. The governments should support the establishing of joint Industry 4.0 collaboration platforms, centers of excellence and incubators to ease the dissemination of knowledge and technology. On academic level, joint research programs and exchange programs should be set up to foster the skilling of labor force in the deployment of Industry 4.0 methods and technologies

Flexible cooperation in non-standard application environments

The integration of preexisting systems into a single, heterogeneous, distributed non-standard application system in domains like office automation or computer-integrated manufacturing are regarded as cooperating systems. They are characterized through teamwork, distribution and the handling of complex data structures (e.g. multimedia data). Object-oriented database systems, providing for complex object management, represent one approach in support of such applications. They concentrate, however, on data modeling aspects and use more or less conventional transaction concepts, based on a global execution control. Hence, they only partially fulfill application requirements as they do not adequately cope with the autonomy that is often inherent to the system's components. As a consequence, we suggest S-transactions as an appropriate means for describing the cooperation of system components in terms of transactions and beyond. In this paper we outline the modeling of conventional transactions (flat or nested as well as distributed and design transactions) in terms of STDL, the S-transaction definition language. Beyond that we point out how to specify SAGAs and similar concepts. Finally we discuss the specification of non-linear but maybe acyclic or even cyclic cooperation structuresPrepared for: Naval Ocean Systems Center and funded by the Naval Postgraduate School.http://archive.org/details/flexiblecooperat00holtO&MN, Direct FundingNAApproved for public release; distribution is unlimited

Stochastic Frontier Analysis Using SFAMB for Ox

SFAMB is a flexible econometric tool designed for the estimation of stochastic frontier models. Ox is a matrix language used in different modules, with a console version freely available to academic users. This article provides a brief introduction to the field of stochastic frontier analysis, with examples of code (input and output) as well as a technical documentation of member functions. SFAMB provides frontier models for both crosssectional data and panel data (focusing on fixed effects models). Member functions can be extended depending on the needs of the user

Assessment of socio-economic functions of tropical lowland transformation systems in Indonesia - sampling framework and methodological approach

EFForTS is a collaborative research center (CRC) which focuses on Ecological and socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems in Sumatra,Indonesia. The paper presents the common sampling frame of the socio economic sub-projects.The investigations and data collections intertwine and complement one another. Thus themethodological approach reflects the idea of an interdisciplinary and integrative research approach. Lead by hypotheses we structured our sampling procedure hierarchically. Starting at the household level in the core villages of the research regions we investigate additional local villages. Further we extend the data collections on the regional level with household, village and trader surveys. The national and international levels we reach by stakeholder interviews with governmental and non-governmental experts. The applied methods are composed of qualitative and quantitative empirical studies

DEMOM- A Media Object Model Incorporating Natural Language Descriptions for Retrieval Support

The DEMOM (Description based Media Object data Model) media object data model aims at providing a uniform framework for managing different types of media data, i.e., images, text, sound or graphics. According to DEMOM media objects are defined as a class hierarchy of objects, i.e., images, text, sound, and graphics being subtypes of the general type media object. Representation specific objects are regarded as subordinate types of the corresponding subtype, e.g. a SUN raster image in pixrect format is an instance of the subtype pixrect which is in turn a subtype of image. Using images as an example we discuss the media object hierarchy, the corresponding access operations and implementation issues. Content oriented search of media data on the basis of predicate calculus is considered as an essential part of DEMOM and hence discussed as wellNaval Ocean Systems Centerhttp://archive.org/details/demonmediaobject00holtO&MN, Direct FundingNAApproved for public release; distribution is unlimited

An SLA-based performance monitoring mechanism for 3PL business process

Asymmetric information between logistics service demanders and logistics service providers may lead to poor service or high service price, and thus cause losses for logistics service demanders. However, a logistics contract is difficult to monitor as a service process in real time. In this paper, SLA management is introduced into business process management of third-party logistics services. Measurement methods for SLA metrics in logistics are analyzed and a monitoring mechanism is proposed as a control program whose main task is to realize the instantiation of SLA metrics. The mechanism is demonstrated by a typical transportation service process of a third party logistics service provider. The measurement process of an SLA metric is then described in detail and the compliance of the logistics SLA is also analyzed and discussed. In the end, the delivery process of a logistics SLA report is given. The proposed monitoring mechanism is an effective method for the monitoring of service level parameters to deliver a proper level of logistics service based on customer requirements. Quality of service can be monitored in real time

Vorrichtung und Verfahren zur Anwesenheitserkennung in Gebäuden

Die Erfindung betrifft eine Anordnung sowie ein Verfahren zur Überwachung und/oder Dokumentation der Aufenthaltsorte, Zeitpunkte und/oder Aufenthaltsdauern eines oder mehrerer beweglicher Objekte in einem Gebäude bestehend aus einer Vielzahl von Räumen (101; 202, 203) und einer Vielzahl von die Räume verbindenden Fluren (204), umfassend eine Vielzahl von in den Räumen und Fluren platzierten Sendern (102; 205, 207, 209) und mindestens ein Empfangsgerät konfiguriert zum Empfang von Signalen der Sender vorzugsweise ohne notwendige Kenntnis des Gebäudegrundrisses und der Raumpläne und ohne notwendige Berücksichtigung von Signalstärken. Das Empfangsgerät bestimmt Aufenthaltsorte anhand der empfangenen Signale sowie anhand einer Zuordnungstabelle, die in den Signalen enthaltenen Identifikationen eindeutig jeweils einen Raum oder einen Flur zuordnet. Die bestimmten Aufenthaltsorte werden zur Erstellung eines Bewegungsprofils an eine zentrale Steuereinheit übertragen