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Mit der Einführung von gesellschaftlichen und politischen Vorgaben wie dem „European Green Deal“ wird die Umsetzung der Kreislaufwirtschaft zur Unternehmensaufgabe. Deren wirtschaftliche Umsetzung erfordert jedoch die Anpassung industrieller Prozessabläufe hinsichtlich des angestrebten Grades an Adaptivität an eine dann zunehmende Varianz von Eingangsmaterialien in die industrielle Wertschöpfung. Strategien wie das Remanufacturing bieten nicht nur ein ökologisches Potenzial, sondern bewirken eine Steigerung der Resilienz und eröffnen dadurch neue wirtschaftliche Geschäftsperspektiven. Innerhalb des Beitrags wird die Bedeutung geeigneter Demontagesysteme für die Kreislaufwirtschaft aufgezeigt. Aufbauend auf den spezifischen Herausforderungen der Kreislaufstrategien wird ein Zielbild für wirtschaftliche Demontagesysteme abgeleitet. Drei industrielle Use Cases zeigen verschiedene Ausprägungen solcher Systeme auf. Es besteht der Bedarf, die Demontage zu automatisieren und gleichzeitig die Adaptivität des Systems zu maximieren, um verschiedenen Produktzuständen gerecht zu werden. Die adaptive automatisierte Demontage stellt hierfür die zentrale Befähigung dar. Zur Umsetzung dienen Befähigertechnologien wie der Einsatz von Sensorik und KI, aber auch das „Design for Disassembly“. Aus organisatorischer Perspektive sind Standardisierungen notwendig, um die Verfügbarkeit von Daten sowohl aus der Produktion, dem User-Zyklus als auch aus automatisierten Zustandsbewertungen als ein Entscheidungsfundament für adaptive Prozesse nutzbar zu machen. Die Bereitstellung und Analyse der notwendigen Daten stellt folglich ein zentrales Anliegen für die Umsetzung der Demontageprozesse dar., With the introduction of social and political requirements such as the "European Green Deal", the implementation of the circular economy is becoming a corporate task. However, its economic implementation as an answer to regulatory demands requires the adaptation of industrial processes regarding the desired degree of adaptivity to a then increasing variance of input materials in industrial value creation. Strategies such as re-manufacturing not only offer ecological potential, but also bring about an increase in resilience and thus open new economic business perspectives. Within the contribution, the importance of suitable disassembly systems including dismantling abilities for the circular economy is shown. Based on the specific challenges of the circular strategies, a target picture for economic disassembly systems is derived. Three industrial use cases show different forms of such systems. There is a need to automate disassembly while maximizing the adaptivity of the system to cope with different product states. Adaptive automated disassembly is the key enabler for this. Enabling technologies such as the use of sensors, AI or "design for disassembly", serve to implement this. From an organizational perspective, standardization is necessary to make data from production, from the user cycle and from automated condition assessments available and usable as a decision-taking foundation for adaptive processes. Consequently, the provision and analysis of the necessary data represents a central concern for the implementation of disassembly processes.

Ethics is concerned with right or wrong and good or evil of human behaviour. It guides man how to become good. What is right is ethical and what is wrong is unethical. Research process includes study design, data collection and data analysis. The analyzed data is published therefore by appropriate body(Redman, 2013).The process is done in an ethical way. The committee on Publication Ethics (COPE) is responsible body with the task of developing appropriate code of conduct (Sengupta & Honavar,2017).Researchers, publishers and editors are guided by it.

Electric vehicles are growing at a significant rate in the world and that makes it essential for modern day electricity networks to be prepared for their integration. A common approach of preparing the network for any kind of demand is to be able to predict or estimate the same based on data and simulations using optimization techniques. This work was aimed at the same in two distinct parts. In the first part, game theoretic methods were tried to be applied to an existing multi agent probabilistic model estimating net demand from electric vehicle. Owing to the complexity of the undertaking, it was decided to only include a payoff based allocation of electric vehicle charging scenarios to estimate electric vehicle demand which accounted for all scenarios rather than all vehicles charging in a single scenario. In the second part, a smaller scenario of an affluent household with two electric vehicles and typical mobility pattern was formulated. Game theory solution concept of Nash Equilibrium was used to optimize the charging of both electric vehicles over a week of usage. The results from the first part, displayed an overall reduction in maximum loads while there were certain shifts in loads observed as well. As an exercise without any inherent optimization mechanism the overall results from this segment were inconclusive. The results from the second part, demonstrated needs for charging the EVs shifting to offpeak hours and charging of vehicles, a maximum of 1-2 times per week based on user range anxiety, game theoretic competition and mobility needs. Further, savings from charging at off-peak tariffs based on time of use electricity tariffs were also evaluated.

Persistent Organochlorine Pesticides in Sediments from Haldi and Rupnarayan River in West Bengal, India