Blockchain-Based Inventory System considering Uncertain Carbon Footprints and Pandemic Effects P. Mala, M. Palanivel, S. Priyan Discrete Dynamics in Nature and Society, 2023 The global supply chain has been severely impacted with the outbreak of COVID-19. The continuous supply of essential products in the post-COVID-19 world is a truly effective and strategic contest. The security and useability of inventory management are a main burden for industries along with the pressure from the government to fulfil the targets of net-zero economy in an uncertain circumstance. One of the most potential keys to these issues is an accurate demand forecasting process by blockchain technology. This article addresses a basic outline for blockchain-based supply chain (SC) and reveals how blockchain technology (BCT) can aid policymakers to cut carbon footprint during and postpandemic time in a fuzzy environment. This study fuzzifies all the carbon factors as intuitionistic triangular fuzzy numbers and uses a signed distance method to defuzzify the model. We consider that the retailer can embrace BCT to enhance demand forecasting. The planned scenario is modeled as an optimization problem to maximize the profit with low carbon emissions and suggest a solution method to solve it. A numerical example is also given to validate the model. We compare the optimal decisions of the SC with and without BCT. We discover that the pandemic and BCT have considerable influences on the optimal results. The study also shows that practitioners should exercise caution when developing operational strategies for maximizing profit with the least amount of carbon emissions during and postpandemic time.
Sustainable Supply Chain System for Defective Products with Different Carbon Emission Strategies Pitchaikani Mala, Muthusamy Palanivel, Siluvayan Priyan, Anuwat Jirawattanapanit, Grienggrai Rajchakit, Pramet Kaewmesri Sustainability Switzerland, 2022 Many nations have created ecological policies and regulations to prevent industries from emitting excessive amounts of carbon emissions into the environment. While significant progress has been achieved in the direction of sustainable growth, many nations still rely on nonrenewable energy sources. This study explores the viability of investing in green technology to achieve the optimal decisions (lot sizes, lead time, and green investment amount) in a two-echelon supply chain system by considering human error with two carbon emission strategies: carbon taxes and limited carbon emissions. It entails the inspection of every shipped lot by the buyer to identify defective products that could have resulted from the vendor’s production process. We show a constrained non-linear program and design a calculus-optimization technique to solve it. The methodology used in this research is the quantitative method, which is based on the principles of operations research, and the models are built on mathematically oriented inventory theory. The results imply that an outsized ecological carbon footprint can be reduced without compromising customer service by designing optimal inventory strategies. The findings also confirm that green investment is the greatest economical method for reducing carbon emissions and system costs.
A cleaner EPQ inventory model involving synchronous and asynchronous rework process with green technology investment S. Priyan, P. Mala, M. Palanivel Cleaner Logistics and Supply Chain, 2022 The amount of carbon emission in the atmosphere continues to grow, and production, storage and transportation are major contributors that are repeatedly unnoticed when it comes to solving the problem. A carbon levy and cap EPQ model has been explored in this study for a controlled carbon emission in view of cleaner production under imperfect production processes where a fraction of the products is faulty. The model incorporates emissions from transportation, production, and storage activities, which are meant to be decreased by green investment. The manufacturer employs a rework approach to rectify the faulty products. Flexible rework allows the manufacturer to choose the rework rate, which can differ from the manufacturing rate, as well as the process of rework, which can be asynchronous or synchronous. A linear rework cost function of the rework rate is assumed. We sought to obtain the lowest cost with respect to optimal lot size, and backorder under the effect of controlling carbon emissions by applying the exponential form of green investment. Keeping these in mind, several mathematical models derived for various rework rate and rework process assumptions with the objective emphases on gaining a trade-off between cost and emissions, thereby finding the optimal production-distribution inventory strategy and an appropriate sustainable plan for handling both synchronous and asynchronous rework process. We show a constrained non-linear programme (NLP) and derive a calculus optimization technique to solve it. An iterative solution technique is used to arrive at the optimal decisions, which are shown analytically and numerically. The results validate the impacts of controlled carbon emissions on the production strategies. The findings mainly suggest that increasing the carbon levy reduces emissions. The firm has more options to decrease emissions caused by industrial activity with the help of green technologies. Although green technology has a higher upfront cost, the producer will reap the advantages of lower emissions.
A sustainable dual-channel inventory model with trapezoidal fuzzy demand and energy consumption S. Priyan, R. Udayakumar, P. Mala, M. Prabha, Ananya Ghosh Cleaner Engineering and Technology, 2022 Most of the consumers relied heavily on e-commerce for products and services for the past few years due to the recent COVID-19 pandemic. This kind of an unexpected behaviour among the consumer society has taken every industry by surprise so that many industries have begun operating online and offline businesses to ensure future competitiveness. Firms introducing online sales are deplorably facing many challenges in terms of logistics and delivery processes, such as short lead times, flexible delivery, capacity of warehouse, and the production process for controlling carbon emissions. Keeping these challenges in mind, a sustainable dual-channel vendor-buyer supply chain model has considered for a controllable emission under fuzzy demand and energy consumption. The model deals with limitation on warehouse floor-space area, and the warehouse divides into two stages such as one for satisfying online orders and the other for satisfying offline orders. The demand rate and energy consumptions are treated as the trapezoidal fuzzy number, and we use the signed distance method to defuzzify the fuzzy joint expected total cost. The objective focuses on obtaining a trade-off between cost and emissions, thereby determining the optimal production-distribution strategy and a proper sustainable plan for handling both online and offline orders. The aforesaid scenario is mathematically formulated in the form of constrained non-linear programme (NLP) and derive a Lagrangean multiplier method to solve it. An iterative solution algorithm is designed, and for better illustration of the developed theory, numerical analysis is carried out followed by a wide discussion on the sensitivity analysis for various parameters. Our results indicate that the optimal solutions of the sustainable fuzzy model slightly fluctuate from the solutions of the sustainable crisp model. According to results, considering the uncertainty in the system is a crucial factor to achieve the economic and environmental sustainability of the production sector. The research reveals that the practitioners should be careful in accounting flexibility in the input factors demand and energy to tackle the uncertainties that always fit the real situation.
Sustainable decision-making approach for dual-channel manufacturing systems under space constraints P. Mala, M. Palanivel, S. Priyan, N. Anbazhagan, Srijana Acharya, Gyanendra Prasad Joshi, Joohan Ryoo Sustainability Switzerland, 2021 In response to the digital revolution, nowadays, many companies operate online and offline businesses in parallel to ensure their future competitiveness. This research examines the inventory strategy for multi-product vendor-buyer supply chain systems, considering space constraints and carbon emissions, in order to improve competence in managing online and offline integrated orders. We amalgamate costs and emissions in transport and storage. Here, we divide the warehouse of the buyer into two stages: one for satisfying online orders and the other for satisfying offline orders. We also assume that additional crashing costs reduce the lead times for receiving products in the buyer’s warehouse. This study demonstrates a mathematical model in the form of a constrained non-linear programme (NLP) and derives a Lagrangian multiplier method to solve it. An iterative solution procedure is designed in order to attain sustainable manufacturing decisions, which are illustrated numerically.
Optimal inventory strategies for two-echelon supply chain system involving carbon emissions and fuzzy deterioration S. Priyan, P. Mala, R. Gurusamy International Journal of Logistics Systems and Management, 2020 The industry sector is an vital direct and indirect source of carbon emissions. Today industries are looking for solutions to reduce carbon emissions associated with their operations. Operational adjustments, such as modifications in batch sizes or order quantities, have proven to be an effective way to decrease emissions. This paper provides a new mathematical model which integrate cost and emissions in transportation and storage to execute optimal operational adjustments for deteriorating products under the framework of two-echelon inventory system. The deterioration rate is treated as the triangular fuzzy number, and we use the extension principle to find the membership function of the fuzzy total cost and defuzzify by the centroid to find the estimate of the total cost in the fuzzy sense. Numerical example is performed to show the effectiveness of the proposed model, and several managerial insights are observed from sensitive analyses which may help both the government and the industry to adopt appropriate carbon reduction regulations.
Multi-echelon Supply Chain Model for Deteriorating Products in a Fuzzy Deterioration Environment S. Priyan, P. Mala Fuzzy Information and Engineering, 2019 Purpose: This research analyses the optimal inventory strategy for a deteriorating product with imprecise deterioration rate in a single supplier-buyer supply chain system with realistic factors. Design/methodology/approach: The integration of production and distribution inventory system is crucial in practice for minimizing a firm's cost while the effect of deterioration cannot be ignored as it affects the entire inventory system. Nowadays managers have begun to recognize that effectively managing deterioration risks in their business operations plays an important role in successfully managing their inventories. Here, the deterioration rate is treated as the triangular fuzzy number. Also we use the extension principle method to define the membership function of the fuzzy total cost and defuzzify by the centroid to find the estimate of the total cost in the fuzzy sense. Findings: A methodology has been proposed through mathematical model which involves designing an iterative algorithm to achieve optimal decisions such as order lot-size and total number of deliveries from the supplier to buyer. Originality value: The effects of varying the central parameter values on the optimal solution are performed by numerical and sensitivity analysis so as to highlight the differences between crisp and the fuzzy cases.
An optimal inventory model with interaction of lot size, production rate and lead-time in a fuzzy back-order system S. Priyan, P. Mala, S. Tiwari RAIRO Operations Research, 2019 This paper examines the decision-making about the interaction of lot size, production rate and lead time between a vendor and a buyer with the consideration of trade credit and fuzzy back-order rate. We assume that the lead time demand is distribution free and the back-order rate is triangular fuzzy number. An economic model is design to determine the optimal lot-size, production rate and lead time while minimizing system total cost. A minimax approach is applied to tackle the model and designed an iterative algorithm to obtain the optimal strategy. Numerical example and sensitivity analyses are given to demonstrate the performance of the proposed methodology and to highlight the differences between crisp and the fuzzy cases. This paper provides optimal decision support tools for managers in the form of mathematical model that improve operational, tactical, and strategic decision making in the fuzzy system. This paper aims to raise the awareness of managers with regard to realistic inventory problems.
Two-warehouse system for non-instantaneous deterioration products with promotional effort and inflation over a finite time horizon M. Palanivel, S. Priyan, P. Mala Journal of Industrial Engineering International, 2018 In the current global market, organizations use many promotional tools to increase their sales. One such tool is sales teams’ initiatives or promotional policies, i.e., free gifts, discounts, packaging, etc. This phenomenon motivates the retailer/or buyer to order a large inventory lot so as to take full benefit of promotional policies. In view of this the present paper considers a two-warehouse (owned and rented) inventory problem for a non-instantaneous deteriorating item with inflation and time value of money over a finite planning horizon. Here, demand depends on the sales team’s initiatives and shortages are partially backlogged at a rate dependent on the duration of waiting time up to the arrival of next lot. We design an algorithm to obtain the optimal replenishment strategies. Numerical analysis is also given to show the applicability of the proposed model in real-world two-warehouse inventory problems.
