Model of Small Medium Enterprises Performance Based on Green Economy Through Strengthening Institutional and Production

This objective of this research is to create a model of Small Medium Enterprises (SMEs) performance based on Green Economy through Production and institutional strengthening. This research is an interactive qualitative research; data collection is done from the primary source through direct interviews, validation data by using this type of credibility, including triangulation of data, methods and theories. The population used in this research is all the Small Medium Enterprises that are located in Sidoarjo. The sampling technique used was purposive sampling by using multiple criteria. From this research found the relationship between production and institutional section against the Small Medium Enterprises performance based on Green Economy. Through the strengthening of production and institutional then the SMEs will have more sustainability in its activities. The conclusions of this research was to Small Medium Enterprises performance based on Green Economy can perform its activities appear to give rise to adverse environmental impacts were then to be done towards strengthening institutional and productio

Lean Practices For Waste Prioritising In Machining Based Product

Many organizations have dedicated to improve the efficiency of operations through waste removal and reduction as a philosophy in the lean manufacturing initiative. This paper aimed to examine the application of lean production techniques in machining based product production systems, particularly for block cross member automotive parts. The Lean tool as known as value stream mapping was deployed for preliminary analysis while the analytical hierarchy process was applied to analyse the multi criteria decision making model for a waste selection process in the production system. The results show that the lean practices' approach by the VSM screened eight waste on the production system, known as Kaizen burst that influence to company’ profit which is high access inventory volume in between process, high rework and reject volume, delayed supplier and deliver product on time to customer, wrong forecast data, changeover time require long time, low machine performance/ inefficiency machine, travelled time in-between process and lack on 5S activities. By using another one of the lean approach, AHP prioritises the waste found into rank and defines the most influenced waste to resolv

Retail Inventory Control Strategies

Despite using computerized merchandise control systems in retail, the rate of stockouts has remained stagnant. The inability to satisfy customer needs has caused a loss of 4% in potential revenue and resulted in dissatisfied customers. The purpose of this qualitative multiple case study was to explore cost-effective inventory control strategies used by discount retail managers. The conceptual framework that grounded the study was chaos theory, which helped identify why some business leaders rely on forecasting techniques or other cost-effective strategies as an attempt to prevent stockouts. The target population was comprised of discount retail managers located throughout northeast Jacksonville, Florida. Purposeful sampling led to selecting 6 retail managers who successfully demonstrated cost-effective inventory control strategies for mitigating stockouts. Data were collected through face-to-face semistructured interviews, company websites, and company documents. Analysis included using nodes to identify similar words and axial-coding to categorize the nodes into themes. Transcript evaluation, member checking, and methodological triangulation strengthened the credibility of the findings. Five themes emerged: (a) internal stockout reduction strategies, (b) external stockout reduction strategies, (c) replenishment system strategies, (d) inventory optimization strategies, and (e) best practices for inventory control. This study may contribute to positive social change by improving inventory management, which may reduce demand fluctuations in the supply chain and reduce logistics costs in the transportation of freight thereby leading to improved customer satisfaction

Strategies to Improve Data Quality for Forecasting Repairable Spare Parts

Poor input data quality used in repairable spare parts forecasting by aerospace small and midsize enterprises (SME) suppliers results in poor inventory practices that manifest into higher costs and critical supply shortage risks. Guided by the data quality management (DQM) theory as the conceptual framework, the purpose of this exploratory multiple case study was to identify the key strategies that the aerospace SME repairable spares suppliers use to maximize their input data quality used in forecasting repairable spare parts. The multiple case study comprised of a census sample of 6 forecasting business leaders from aerospace SME repairable spares suppliers located in the states of Florida and Kansas. The sample was collected via semistructured interviews and supporting documentation from the consenting participants and organizational websites. Eight core themes emanated from the application of the content data analysis process coupled with methodological triangulation. These themes were labeled as establish data governance, identify quality forecast input data sources, develop a sustainable relationship and collaboration with customers and vendors, utilize a strategic data quality system, conduct continuous input data quality analysis, identify input data quality measures, incorporate continuous improvement initiatives, and engage in data quality training and education. Of the 8 core themes, 6 aligned to the DQM theory\u27s conceptual constructs while 2 surfaced as outliers. The key implication of the research toward positive social change may include the increased situational awareness for SME forecasting business leaders to focus on enhancing business practices for input data quality to forecast repairable spare parts to attain sustainable profits

Monitasoisen varastojärjestelmän hallinnan parantaminen varaosaliiketoiminnassa

The research question of this thesis was: How to reduce current inventory levels by actions found from literature without decreasing customer satisfaction? The aim was to investigate the Case Company’s multi-echelon inventory system through quantitative methods. To address the research question, relevant literature research is also needed. In the first chapters, a theoretical background is conducted as the lateral empirical phase. Scientific journals and articles are used as the base of the theoretical background. The purpose of the theoretical background is to cover the most important issues of warehousing management and item stocking decisions in a multi-echelon inventory in respect to the situation of The Case Company. The empirical part of this thesis starts with a description of the case company’s current inventory management principles. Then, the current situation is evaluated by key performance indicators in order to find the most problematic item groups. Data for this part was gathered from the Case Company’s reporting system. Upon knowing the current situation, actions for improvement are then analysed in a subsequent empirical phase. The result of the current situation is that every front line unit stock value consists mostly of locally non- or low-moving items in which case the relevant literature recommends downstream echelons to concentrate on high-moving items and distribution center (DC) distributes locally low moving items. When evaluated which locally low-moving items are returnable, the results show that front line units could reduce their inventory value by almost 25% even though the stock levels for high moving items were increased. During the data gathering and analysing process, multiple areas of improvements were also found. Firstly, the reporting system needs improvement because it does not show front line unit performance by local indicators. Furthermore, the reporting system does not include all order lines in its reports and some of the ordered lines are incorrect. Secondly, the Case Company should review its KPIs. The Case Company should add perfect order KPI indicator to achieve more accurate information about its performance. Lastly, purchasing policies need to be changed in front line units. The distribution center has shown its superiority especially in low moving items and thus it is recommended that DC is used more than it is currently as a default vendor

Risk Assessment of Deadly Economic Socio-Political Crisis with Correlational Network and Convolutional Neural Network

From social analysis to biology to machine learning, graphs naturally occur in a wide range of applications. In contrast to studying data one at a time, graphs' unique capacity to capture structural relationships among data enables them to yield additional insights. Nevertheless, the capacity to learn from graphs can be difficult because meaningful connectivity should exist between data and the form of data such as text, numbers or categories should allow for building a graph from their relationships. Investigating hidden patterns in the variation of development indicators and severe socio-political crises that happened in low-income countries is an analytical approach that has been experimented with in this research. Evidence of a correlation between socio-political crises and development indicators suggests that a method to assess the risk of crisis should consider the context of each country, as well as the relative means of crisis. This research reviewed different risk assessment methods and proposed a novel method based on a weighted correlation network, and convolution neural network, to generate images representing the signature of development indicators correlating with a crisis. The convolution neural network trained to identify changes in indicators will be able to find countries with similar signatures and provide insights about important indicators that might reduce the number of deadly crises in a country. This research enhances the knowledge of developing a quantitative risk assessment for crisis prevention with development indicators

Prozessverbesserungen im Ersatzteilmanagement unter dem Einfluss von Informationsdefiziten

Die schnelle Verfügbarkeit von Ersatzteilen hat einen maßgeblichen – wenn auch indirekten – Anteil an der Wertschöpfung produzierender Unternehmen. Kommt es zu einem ungeplanten Stillstand der Produktionsanlagen, kann dies schnell zu Kosten in einer kaum zu überschauenden Höhe führen, sollte die Ursache des Ausfalls, z. B. eine defekte oder verschlissene Komponente, nicht zeitnah behoben werden können. Lange Primärproduktlebenszyklen bei gleichzeitig abnehmenden Zeiträumen zwischen Innovationen in Bezug auf Maschinen bewirken zudem einen Anstieg des Umfangs von Ersatzteilsortimenten. In der Folge wird insb. das Bestandsmanagement der Akteure auf dem Ersatzteilmarkt vor große Herausforderungen gestellt. Dessen Handling sollte etwa durch gezielte Klassifizierungen und Bedarfsprognosen erleichtert werden. Diese Ausgangslage bildet bereits seit Jahrzehnten den Nährboden für die Herausbildung vielfältiger wissenschaftlicher Entscheidungsunterstützungsmodelle innerhalb des Ersatzteilmanagements. Die teils hohe Komplexität der Verfahren und der Umstand, dass sie häufig mit einem umfassenden Input an Daten und Informationen einhergehen, förderten die Entstehung einer in der Literatur immer wieder erwähnten Forschungslücke zwischen Wissenschaft und Praxis. Das Ziel der vorliegenden Arbeit ist es, einen Beitrag zur Schließung ebendieser Forschungslücke zu leisten. Im Schwerpunkt erfolgt eine Auseinandersetzung mit Informationsdefiziten, welche die Umsetzung von Prozessverbesserungen hemmen. Hierzu wird sich zum einen auf eine umfassende Recherche existenter theoretischer Beiträge gestützt. Praktisch motivierte Forschungsbeiträge repräsentieren in diesem Zusammenhang den Schwerpunkt eines extensiven Literature Reviews. Darauf aufbauend werden zum anderen qualitative Fallstudien mit Maschinenbetreibern, Primärproduktherstellern und aufarbeitend tätigen Unternehmen durchgeführt sowie hinsichtlich des Zusammenhangs zwischen angestrebten Prozessverbesserungen und Informationsdefiziten analysiert. Die Auswertung kulminiert in Schlussfolgerungen zu potenziellen Faktoren, die Einfluss auf das Informationsmanagement bei der Beseitigung der Defizite nehmen können. Das eigens entwickelte Framework zum Ersatzteil-Informationsmanagement stellt die Vereinigung der theoretischen sowie praktischen Erkenntnisse dar und wird schließlich am Beispiel eines Gebrauchtmaschinenhändlers angewandt