Modeling the Multi-channel Section in the Supply Chain System using the Multiserver Queue Analogy

The industry generally consists of a supply chain system. The main constituents of any supply chain system are suppliers, manufacturers, distribution centers, and retailers. The system configuration can be straight chain, branched, cyclic, or a combination of all. An analytical model is needed to study system behavior as a result of the dynamics of its constituents. Modeling a multi-channel section becomes quite a challenging job in this regard. A method of modeling the multi-channel section will be discussed in this paper by adopting multi-server queues. As is well known, in a multi-server queue, there is a branching point at which the flow of entities begins to spread across several parallel servers. In the modeling perspective of this paper, the branching point is in the buffer (finished good warehouse in the factory, i.e., the focal echelon). That is the end of the waiting line from which the entity specifically moves to one of the servers, or in this context; it is called a channel. In this paper, the number of channels can be any, generalizable, can be more than two. Hence, the subsystem studied includes a factory, finished product warehouse, and several distribution centers. The factory produces by the mechanism of, where and r are stopping point and production restarting point, respectively. Production stops when the quantity of finished product in the warehouse reaches units and will restart the production when the quantity drops to the same or lower than units. The model is developed under Markovian assumptions by considering the quantities of production rates, the number of distribution centers (channels), travel time from factories to each distribution center, delivery lot size, and the time between the arrival of orders from distribution centers. The system under study is seen as a case of two echelons, namely factories and distribution channels. The numerical model obtained is applied to one case example with certain conditions. Comparisons with discrete simulation results give relatively small and acceptable differences. So, in the future, this model can complement the overall modeling of the supply chain system, a multi-echelon system with multi-channel distribution.

New Product Development Method Trends and Future Research

Research on new product development (NPD) has led to tools, methods, models, and frameworks that enable researchers to develop better products. However, a comprehensive review of the methods, models and frameworks related to NPD is lacking. This literature study aims to identify research trends, methods, and frameworks used in NPD between 2010 and 2019. A systematic literature review is conducted by developing a structured research protocol. An analysis of 50 selected papers shows that research on NPD can be categorized into 15 conceptual papers, six review papers, 28 case studies, and one survey paper. This paper provides an overview of each tool and presents future research opportunities. This paper concludes that future research can be directed toward combining several methods to design products that satisfy consumer desires with shorter design times, aspects of NPD collaboration, and aspects of changing consumer preferences.

Developing A Group Model Building Causal Loop Diagram to Understand Millennial Generation Trust in Twitter as Early Warning System for Natural Disaster

Nowadays, Twitter is used as an Early Warning System (EWS) for disasters because of the speed and many users. Based on Asosiasi Penyedia Jasa Internet Indonesia (APJII) data, in 2017, almost 50% of internet users in Indonesia are born in 1983-1998. They are called the millennial generation. Therefore, this study aims to explore the trust of millennials towards Twitter as an EWS. This study utilizes the conceptual model from System Dynamics named Causal Loop Diagram (CLD) to identify the factors and the causal relationship among millennials' factors to trust Twitter as an EWS. It involves ten participants from the millennial generation, consisting of five passive Twitter users and five active Twitter users. A semi-structured interview was conducted with all participants to build the initial CLD gathered from each participant's perspective. Afterward, the initial CLD was verified by all participants through Focus Group Discussion. A group model building CLD that represents the influencing factors and their causal relationship of millennial generation trust in Twitter as EWS for a natural disaster is successfully developed from this study. The tweet frequency, the number of followers, the account credibility, the verified account, the level of trust in social media, and the content quality are considered the underlying factors of active and passive users to trust in Twitter as an EWS natural disaster.

Predicting the Readiness of Indonesia Manufacturing Companies toward Industry 4.0

This research discusses Indonesia's readiness to implement industry 4.0. We classified the Indonesia manufacturing companies' readiness, which is listed in the Indonesia Stock Exchange, in industry 4.0 based on the 2018 annual reports. We considered 38 variables from those reports and reduced them using principal component analysis into 11 variables. Using clustering analysis on the reduced dataset, we found three clusters representing the readiness level in implementing industry 4.0. Finally, we used the decision tree for analysing the classification rules. As the finding of this study, Total book value of the machine is the variable that defined the readiness of a company in industry 4.0. The bigger those values are, the more ready a company to compete in industry 4.0. The other measures, i.e., Total cost of revenue by total revenue; Direct labor cost; Total revenue/Total employee and Transportation cost/Total revenue, will define the readiness of a manufacturing company to transform into industry 4.0. or not ready to transform into industry 4.0.

The Unrelated Parallel Machine Scheduling with a Dependent Time Setup using Ant Colony Optimization Algorithm

The unrelated parallel machine scheduling (PMS) problem is essential for the manufacturing industry. Scheduling will save company resources, especially time management. By solving scheduling problems quickly and precisely, the company can get more profit. On that note, this paper focused on unrelated PMS problems, which did not consider the inherent uncertainty in processing time and set up time by minimizing the makespan and tardiness. This paper aimed to minimize the makespan and tardiness using timing considerations. This paper described how to schedule unrelated parallel machines using the Ant Colony Optimization (ACO) Algorithm approach. The ACO is beneficial for inherent parallelism problems and can provide fast and reasonable solutions. This study revealed that the results of ACO Algorithm scheduling were obtained under a steady condition in iteration 30467. This condition can be interpreted that the makespan and tardiness value is close to 2.75%. By minimizing the makespan and tardiness, the delay of product delivery to consumers can be anticipated. Moreover, a company can maintain customer satisfaction and increase its profit.

Multi-Objective Optimization of Machining Parameters for Multi-Pass CNC Turning to Minimize Carbon Emissions, Energy, Noise and Cost

Global warming is a huge environmental issue today. This is due to the high level of world carbon emissions. The manufacturing process accounts for 30% of the world's carbon emissions production. Sustainable manufacturing is necessary to implement to reduce carbon emission levels caused by the manufacturing process. There are three aspects of sustainable manufacturing, namely environmental aspects, economic aspects, and social aspects. These three aspects can be implemented in the machining process by optimizing machining parameters in multi-pass CNC turning. This research aims to optimize CNC turning machining parameters by considering energy consumption, carbon emissions, noise, and production cost. The model is solved using a Multi-objective Genetic Algorithm in Matlab 2016b then the transformation and weighting functions are carried out from the feasible value. Based on the optimization results, the total energy consumption value obtained is 2.50 MJ; total production cost is $ 2.19; total carbon emissions are 5.97 kgCO2, and noise is 236, 19 dB. The sensitivity analysis exhibits the machining parameters that affect the objective function: The cutting speed parameter and the feed rate parameter. This model can be used to improve the manufacturing process and support sustainable manufacturing.

Influence of Information Quality on Retailer Satisfaction through Supply Chain Flexibility and Supplier Relationship Management in the Retail Industry

Businesses always compete to improve customer satisfaction. A firm engaged in as a distributor as well, always try to provide satisfaction to their customer, in this case, retailer and wholesales. The distributor can improve retailer satisfaction by providing such information that suits retailer requirements in the pursuit that the supply chain flow can move quickly, particularly on the flow of products from the manufacturing ordered by the distributors. This study aims to obtain a relationship between distributors and retailer companies. This study surveyed 100 retailers, and wholesale companies engaged in Fast Moving Consumer Goods (FMCG) and the supplier domiciled in the city of Makassar, South Sulawesi, with revenues of more than IDR 300,000,000. - / year. SmartPLS software version 2.0 was used to test the hypothesis. The results of the study found that information quality can provide a positive increase in improving supplier relationship management. Adequate information quality cannot significantly increase supply chain flexibility and retailer satisfaction. Supplier relationship management built by distributors can have an impact of 0.611 on supply chain flexibility in retail and retail satisfaction companies of 0.367. The stronger distributor and retailer relationship can increase distributor flexibility and retail satisfaction. Supply chain flexibility built by distributor companies can have a significant impact on retailer satisfaction of 0.463. This research provides an improvement in the development of supply chain management theory, in particular, building relationships with customers.

System Dynamic Approach to Improve Emergency Response in Humanitarian Logistics in Indonesia

Volatile and vulnerable conditions during disaster relief cause many problems on the coordination of aid replenishments. Research states that partnership improves coordination thus reducing the uncertainty condition along supply chain including in replenishment. This paper aims to fulfill the research gap on examining the impact of partnership in the disaster relief process. Dynamic characteristics model of this case was built by modifying the beer distribution game through Vensim PLE Plus. Model had been validated and verified with the West Java Regional Disaster Management Authority (BPPD). The simulation was run for for two types of product: repetitive demand (food package) and one-time demand (blanket). Total cost, bullwhip effect, and total distribution time for each scenario are then compared. The simulation results show that the proposed scenario, which is developed based on the usage of blockchain on the partnership system, can reduce the total distribution time for about 43% for blanket and 27% for food package. Meanwhile, the total cost for blankets can be reduced for about 29% and 13% for food packages. But on the other side, the partnership system had aggravated the bullwhip effect. Some future potential researches are also proposed in this study.

Does the Ease of Starting a New Business Affect Country’s Financial Vulnerability? Evidence from Eight European Economies

This paper investigates whether indicators on the ease of doing business explain variation of financial system vulnerability amongst eight biggest European economics between 1999 and 2014. Using mixed-effects estimation method for sectoral observations nested within countries, the results suggest that easy access to get credit is associated with increased financial vulnerability, as measured by decreased excess return in equity market. The significance of political stability, regulatory quality, and rule of law also marks the role of institutional environment towards vulnerability by facilitating the openness towards new business. Finally, a high degree of openness is not always good especially if they are combined with better institutional environment. This confirms the importance of the level of openness, as well as its channels, in determining the extent of vulnerability.

Integrating Human Behavior and Safety Measure into Evacuation Route Planning in a Volcanic Crisis

Many traditional methods in evacuation route planning are motivated by the operational objective, such as total travel/clearance time. Little attention has been given to the human factor and the safety aspect of the evacuees during the planning phase. Our study aims to propose a simple yet practical route planning method that simultaneously considers human behavior, safety factor, and the travel time in a volcanic crisis context. The planning model is developed based on the shortest-path problem with a joint-cost parameter representing the three aspects. We present a large-scale street network in Merapi volcano as a case study. The result implies that employing a joint-cost parameter is effective for creating an evacuation route that is reasonably safe and in line with human cognition in navigation. The finding offers practical insights for the stakeholders as part of the greater effort to develop a systematic disaster management plan.