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Inventory Management for Sustainable Industrial Operations

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 53198

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Special Issue Editors

Dr. Riccardo Patriarca

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Guest Editor

Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy
Interests: resilience management; resilience engineering; safety and risk management; socio-technical systems modelling; operations management; aviation; supply chain management
Special Issues, Collections and Topics in MDPI journals

Dr. Giulio Di Gravio

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Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy
Interests: supply chain management; industrial operations and management; compliance and risk management; resilience engineering; performance variability in complex systems; product-service system (PSS)
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Francesco Costantino

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Guest Editor

Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Rome, Italy
Interests: inventory management; supply chain management; logistics; resilience management; information management; risk management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Effective inventory management strategies aim to reduce costs while ensuring high service levels. At the same time, environmental and social aspects of inventory management should be considered to jointly ensure sustainability and profitability.

This Special Issue aims to be a dedicated point of reference for researchers working in the inventory management domain and to provide policy-makers with insights on advanced techniques in the field, with the ultimate target of strengthening the link between research and practice.

The purpose of this Special Issue is to gather knowledge on inventory management for both spare parts and consumable items. Particular attention is devoted to items’ transportation, warehousing, degradation, and demand forecast, especially in relation to emissions and environmental management.

Relevant contributions should investigate alternative inventory management strategies in relation to cost, availability, and environmental sustainability, either at the theoretical or operational level. Analytical or simulation models would be particularly welcome, especially if adopting a systemic view to support supply chain decision-makers on, e.g., lead times, reorder quantities, and stock levels.

References

Chan, F.T.S., Li, N., Chung, S.H., Saadat, M. Management of sustainable manufacturing systems-a review on mathematical problems. Int. J. Prod. Res. 2017, 55 (4), 1210–1225.

Fichtinger, J., Ries, J.M., Grosse, E.H., Baker, P. Assessing the environmental impact of integrated inventory and warehouse management. Int. J. Prod. Econ. 2015, 170, 717–729.

Patriarca R, Costantino F, Di Gravio G. Inventory model for a multi-echelon system with unidirectional lateral transshipment. Expert Syst. Appl. 2016, 65, 372–382.

Patriarca R, Costantino F, Di Gravio G, Tronci M. Inventory optimization for a customer airline in a Performance Based Contract. J. Air Transp. Manag. 2016, 57, 206–216.

Pourhejazy, P., Kwon, O.K. The new generation of operations research methods in supply chain optimization: A review. Sustainability (Switzerland), 2016, 8 (10), art. no. 1033.

Sherbrooke CC. Optimal Inventory Modeling of Systems: Multi-Echelon Techniques. Springer: New York, NY, USA, 2004.

Tiwari, S., Daryanto, Y., Wee, H.M. Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. J. Clean. Prod. 2018, 192, 281–292.

Dr. Riccardo Patriarca
Prof. Dr. Giulio Di Gravio
Prof. Dr. Francesco Costantino
Guest Editors

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Keywords

Spare parts management
Consumable parts management
Inventory management
Operations management
Green supply chain
Emissions management
Sustainable operations
Warehouse
Transportation
Inventory pooling
Performance-based contract
Maintenance management
Item degradation
Systemic methods
Analytical models
Simulation models

Published Papers (13 papers)

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Research

21 pages, 1096 KiB

Open AccessArticle

Optimization of Storage Location Assignment for Non-Traditional Layout Warehouses Based on the Firework Algorithm

by Xuan Zhang, Tiantian Mo and Yougong Zhang

Sustainability 2023, 15(13), 10242; https://0-doi-org.brum.beds.ac.uk/10.3390/su151310242 - 28 Jun 2023

Cited by 4 | Viewed by 1487

Abstract

With the development of logistics, sustainable warehousing has become increasingly important. To promote the warehousing efficiency, non-traditional layout warehouses and storage location assignments have been proposed separately. However, they are rarely combined. Taking inspiration from the advantages of non-traditional layout warehouses and storage location assignments, a storage location assignment optimization algorithm for non-traditional layout warehouses is proposed to further improve the efficiency and sustainability of warehousing. By reducing the picking distance and picking time, this algorithm further boosts the warehouse efficiency and sustainability, saving energy in the process and resulting in positive effects on the environment and the economy. In the process of establishing the model, taking the order-picking efficiency and shelf stability as optimizing objectives, a multi-objective optimization model is derived. Then, a storage location assignment optimization algorithm based on the firework algorithm is developed using adaptive strategies for explosion and selection to enhance the convergence rate and optimization performance of the algorithm. With this approach, the storage location assignment optimization for non-traditional layout warehouses can be handled well. Finally, a set of comparative simulations is carried out with MATLAB, and the results show various positive effects for sustainable warehouse management, such as a higher order-picking efficiency, better shelf stability, time and resource savings, and so on. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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25 pages, 1533 KiB

Open AccessArticle

An Efficient Approach to Investigate the Tradeoff between Double Handling and Needed Capacity in Automated Distribution Centers

by Mohammed Alnahhal, Bashir Salah and Mohammed Ruzayqat

Sustainability 2022, 14(13), 7678; https://0-doi-org.brum.beds.ac.uk/10.3390/su14137678 - 23 Jun 2022

Cited by 2 | Viewed by 1752

Abstract

Sustainable techniques in distribution centers, such as automation that reduces the land area needed, can be utilized. Automated Storage and Retrieval Systems (AS/RS) are used to efficiently manage the flow of pallets and carton cases in distribution centers. There are two types of AS/RS: one for pallets and another type for cases that are depalletized from pallets. Further enhancements on the system are obtained by investigating both warehouses together. This paper investigates an efficient approach that directly affects the conceptual design of automated distribution centers for the purpose of reducing the total costs. The tradeoff between the throughput (defined by the level of double handling) and warehouse capacity is investigated in this study by finding the best lot sizing rules for different classes of products (A, B, and C). These rules are to determine the method of moving carton cases from the first warehouse to the second one. The number of stacker cranes is determined based on the found throughput. The effect of double handling of pallets on the design is considered for the first time in this study. Analytical formulas and simulation were used to find the throughput and capacity based on the mentioned lot sizing rules. Then, an integer nonlinear model was developed to optimize the system. According to the results of the assumed data, the model can save up to 19.5%. The costs of stacker cranes were found to account for approximately 78.7% of the total costs in the best solution found. A decision support system has been developed to help decision makers find an efficient design of distribution center. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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16 pages, 4854 KiB

Open AccessArticle

Increasing Throughput in Warehouses: The Effect of Storage Reallocation and the Location of Input/Output Station

by Mohammed Alnahhal, Bashir Salah and Rafiq Ahmad

Sustainability 2022, 14(8), 4611; https://0-doi-org.brum.beds.ac.uk/10.3390/su14084611 - 12 Apr 2022

Cited by 4 | Viewed by 1833

Abstract

Automatic warehousing systems are a sort of green technology that is becoming increasingly popular in the logistics business. Automated Storage/Retrieval Systems (AS/RS) are one of the most significant components of advanced automated logistics and manufacturing systems. The majority of AS/RS systems use input/output (I/O) points located in the lower left corner of the rack. These systems are reaching their maximum capacity because of their layout design limitations. Breakthrough solutions are needed to enhance the performance of existing systems. In this study, we examined how the location of I/O station can affect the total travel time. Another strategy for enhancement is a two-step preparation method. In this strategy, the allocation of the storage is changed, in the idle time, to be closer to the I/O point to reduce the service time for a class-based storage assignment. An analytical model was used to introduce for the first time optimal configurations of this strategy. We tested the suggested strategy using a simulation model created using R software, specifically designed for this purpose. Results showed that the two-step preparation strategy took between 1.2 and 1.9 h before the shift starts. The enhancement on throughput is almost the same for both possible locations of the I/O point. The results also showed that the two strategies (location of the I/O point and reallocation of storage) could increase throughput by about 21% to 28%, depending on parameters such as the number of orders and the height of the storage rack. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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16 pages, 3196 KiB

Open AccessArticle

Total Costs of Centralized and Decentralized Inventory Strategies—Including External Costs

by Dariusz Milewski

Sustainability 2020, 12(22), 9346; https://0-doi-org.brum.beds.ac.uk/10.3390/su12229346 - 10 Nov 2020

Cited by 7 | Viewed by 4840

Abstract

The paper deals with the economic efficiency of decentralized and centralized strategies of distribution goods in terms of both internal efficiency of firms and external costs of logistics processes (first of all external costs of transport). The author developed a model (using an electronic spreadsheet) in order to calculate the economical efficiency in the micro and macro dimensions in order to find the distances on which distribution using one central warehouse is more profitable than decentralized distribution. The results of the simulations show that the strategy of centralized inventories can be in many cases an economically effective strategy although not for deliveries on very long distance. The results confirm that the benefits of centralization are lower inventories, although the simulations do not confirm the applicability of the square root law to calculate the level of inventories. However, they confirm a positive impact on the level of logistic customer service, measured by the availability of stocks. Better service is probably the main benefit of this strategy. In order to investigate the impact of individual parameters on the total costs of logistics processes 1300 simulations were carried out for various cases: The volume of annual sales, fluctuations in demand, the value of distributed goods, the number of warehouses in a decentralized system and the width of the product range, costs of warehousing, and maintaining stocks, and the distance of transport and in deliveries to customers. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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17 pages, 19199 KiB

Open AccessArticle

Towards Forklift Safety in a Warehouse: An Approach Based on the Automatic Analysis of Resource Flows

by Alessandra Cantini, Filippo De Carlo and Mario Tucci

Sustainability 2020, 12(21), 8949; https://0-doi-org.brum.beds.ac.uk/10.3390/su12218949 - 28 Oct 2020

Cited by 11 | Viewed by 5425

Abstract

Warehouse management is a discipline that has gained importance in recent decades. In the era of the Digital Revolution and Industry 5.0, to enable a company to attain a competitive advantage, it is necessary to identify smart improvement tools that help search for warehouse problems and solutions. A good tool to highlight issues related to layout and resource flows is the spaghetti chart which, besides being used to minimize waste according to lean philosophy, can also be used to assess warehouse safety and reliability and improve the plant sustainability. This article shows how to exploit “smart spaghetti” (spaghetti chart automatically generated by smart tracking devices) to conceive improvements in the layout and work organization of a warehouse, reducing the risk of collision between forklifts and improving the operators’ safety. The methodology involves automatically mapping the spaghetti charts (searching for critical areas where the risk of collision is high) and identifying interventions to be carried out to avoid near misses. “Smart spaghetti” constitutes a valuable decision support tool to identify potential improvements in the system through changes in the layout or in the way activities are performed. This work shows an application of the proposed technique in a pharmaceutical warehouse. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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12 pages, 213 KiB

Open AccessArticle

Destruction Decisions for Managing Excess Inventory in E-Commerce Logistics

by Pourya Pourhejazy

Sustainability 2020, 12(20), 8365; https://0-doi-org.brum.beds.ac.uk/10.3390/su12208365 - 12 Oct 2020

Cited by 20 | Viewed by 6376

Abstract

The Internet has brought about new possibilities for innovation and radically changed business activities. Internet shopping is a prime example of increasing popularity, which is exacerbated due to the recent pandemic. It is expected that e-commerce will accommodate more than a quarter of the total retail sales worldwide in the next few years. Given the characteristics of e-commerce, inventory management is of paramount importance for an effective and timely response to the online customers’ demand. Despite its relevance, the issue of warehouse excess inventory is not sufficiently studied in the operations management literature. This study explores the factors, including sustainability and strategic considerations, that influence the inventory destruction decisions as one of the alternatives for managing excess inventory. Applying the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, the interrelationships between the decision factors are investigated and the decisive considerations are identified. Overall, the outcomes provide insights for the e-commerce practitioners and offer directions for modeling and managing inventory destruction decisions. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

19 pages, 2297 KiB

Open AccessArticle

Improved MRO Inventory Management System in Oil and Gas Company: Increased Service Level and Reduced Average Inventory Investment

by Usman Ali, Bashir Salah, Khawar Naeem, Abdul Salam Khan, Razaullah Khan, Catalin Iulian Pruncu, Muhammad Abas and Saadat Khan

Sustainability 2020, 12(19), 8027; https://0-doi-org.brum.beds.ac.uk/10.3390/su12198027 - 29 Sep 2020

Cited by 9 | Viewed by 7557

Abstract

This study proposes a methodology for the oil and gas businesses to keep their production plant productive with a minimum investment in carrying maintenance, repair, and operating inventory planning. The goal is to assist the exploration and production companies in minimizing the investment in keeping maintenance, repair, and operating (MRO) inventory for improving production plant uptime. The MRO inventory is the most expensive asset and it requires substantial investment. It helps in keeping the oil and gas production plant productive by performing planned and unplanned maintenance activities. A (Q, r) model with a stock-out and backorder cost approach is combined with a continuous inventory review policy for the analysis of class A items of oil and gas production plant MRO inventory. The class A items are identified through popular ABC analysis based on annual dollar volume. The demand for the inventory is modeled through Poisson distribution with consideration of constant lead time. The (Q, r) model in both stock-out cost and backorder cost approaches assigned higher order frequency and lower service level to low annual demand and highly expensive items. The stock-out cost approach shows an 8.88% increase in the average service level and a 56.9% decrease in the company average inventory investment. The backorder cost approach results in a 7.77% increase in average service level and a 57% decrease in average inventory investment in contrast to the company’s existing inventory management system. The results have a direct impact on increasing plant uptime and productivity and reducing company maintenance cost through properly managing maintenance stock. The analysis is carried out on the oil and gas production plant’s MRO inventory data, but it can be applied to other companies’ inventory data as well. All the results reflected in this research are based on the inventory ordering policy of two orders per year. The inventory ordering frequency per year may be other than two orders per year depending on the type of organization. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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27 pages, 2526 KiB

Open AccessArticle

Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand

by Ahmed Shaban, Mohamed A. Shalaby, Giulio Di Gravio and Riccardo Patriarca

Sustainability 2020, 12(16), 6470; https://0-doi-org.brum.beds.ac.uk/10.3390/su12166470 - 11 Aug 2020

Cited by 7 | Viewed by 2877

Abstract

The bullwhip effect reflects the variance amplification of demand as they are moving upstream in a supply chain, and leading to the distortion of demand information that hinders supply chain performance sustainability. Extensive research has been undertaken to model, measure, and analyze the bullwhip effect while assuming stationary independent and identically distributed (i.i.d) demand, employing the classical order-up-to (OUT) policy and allowing return orders. On the contrary, correlated demand where a period’s demand is related to previous periods’ demands is evident in several real-life situations, such as demand patterns that exhibit trends or seasonality. This paper assumes correlated demand and aims to investigate the order variance ratio (OVR), net stock amplification ratio (NSA), and average fill rate/service level (AFR). Moreover, the impact of correlated demand on the supply chain performance under various operational parameters, such as lead-time, forecasting parameter, and ordering policy parameters, is analyzed. A simulation modeling approach is adopted to analyze the response of a single-echelon supply chain model that restricts return orders and faces a first order autoregressive demand process AR(1). A generalized order-up-to policy that allows order smoothing through the proper tuning of its smoothing parameters is applied. The characterization results confirm that the correlated demand affects the three performance measures and interacts with the operating conditions. The results also indicate that the generalized OUT inventory policy should be adopted with the correlated demand, as its smoothing parameters can be adapted to utilize the demand characteristics such that OVR and NSA can be reduced without affecting the service level (AFR), implying sustainable supply chain operations. Furthermore, the results of a factorial design have confirmed that the ordering policy parameters and their interactions have the largest impact on the three performance measures. Based on the above characterization, the paper provides management with means to sustain good performance of a supply chain whenever a correlated demand pattern is realized through selecting the control parameters that decrease the bullwhip effect. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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19 pages, 3385 KiB

Open AccessArticle

Learning from Incidents: A Supply Chain Management Perspective in Military Environments

by Raffaele Cantelmi, Giulio Di Gravio and Riccardo Patriarca

Sustainability 2020, 12(14), 5750; https://0-doi-org.brum.beds.ac.uk/10.3390/su12145750 - 17 Jul 2020

Cited by 3 | Viewed by 3820

Abstract

Supply chain management (SCM) represents a crucial role in the military sector to ensure operation sustainability. Starting from the NATO handbook for military organizational learning, this paper aims at investigating the link between technical inconveniences and sustainable supply chain operations. Taking advantage of the learning from incidents (LFI) models traditionally used in the risk and safety management area, this paper proposes an information management system to support organizational learning from technical inconveniences in a military supply chain. The approach is discussed with reference to the Italian context, in line with international and national standards for technical inconvenience reporting. The results of the paper show the benefits of adopting a systematic LFI system for technical inconveniences, providing related exemplar business intelligence dashboards. Further implications for the generalization of the proposed information management system are presented to foster a healthy and effective reporting environment in military scenarios. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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19 pages, 489 KiB

Open AccessArticle

Multicriteria ABC Inventory Classification Using the Social Choice Theory

by Fan Liu and Ning Ma

Sustainability 2020, 12(1), 182; https://0-doi-org.brum.beds.ac.uk/10.3390/su12010182 - 24 Dec 2019

Cited by 19 | Viewed by 4420

Abstract

The multicriteria ABC inventory classification has been widely adopted by organizations for the purpose of specifying, monitoring, and controlling inventory efficiently. It categorizes the items into three groups based on some certain criteria, such as inventory cost, part criticality, lead time, and commonality. There has been extensive research on such a problem, but few have considered that the judgments about criteria’s importance order usually exhibit a substantial degree of variability. In light of this, we propose a new methodology for handling the multicriteria ABC inventory classification problem using the social choice theory. Specifically, the pessimistic and optimistic results for all possible individual judgments are obtained in a closed-form manner, which are then balanced by the Hurwicz criterion with a “coefficient of optimism”. The CRITIC (Criteria Importance Through Intercriteria Correlation) method is used to aggregate the individual judgments into a collective choice, according to which the items are classified into Groups A, B, and C. Through a numerical experiment, we show that the proposed methodology not only considers all possible preferences among the criteria, but also generates flexible classification schemes. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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15 pages, 2891 KiB

Open AccessArticle

A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution

by Riccardo Patriarca, Tianya Hu, Francesco Costantino, Giulio Di Gravio and Massimo Tronci

Sustainability 2019, 11(19), 5180; https://0-doi-org.brum.beds.ac.uk/10.3390/su11195180 - 21 Sep 2019

Cited by 9 | Viewed by 2327

Abstract

Optimal spare parts management strategies allow sustaining a system’s availability, while ensuring timely and effective maintenance. Following a systemic perspective, this paper starts from the Multi-Echelon Technique for Recoverable Item Control (METRIC) to investigate the potential use of a Weibull distribution for modelling items’ demand in case of failure. Adapting the analytic formulation of METRIC through a Discrete Weibull distribution, this study originally proposes a METRIC-based model (DW-METRIC) to be used for modelling the stochastic demand in multi-item systems, in order to ensure process sustainability. The DW-METRIC has been tested in a case study related to an industrial plant constituted by 98 items in a passive redundancy configuration. Comparing the results via a simulation model, the outcomes of the study allow defining applicability criteria for the DW-METRIC, in those settings where the DW-METRIC offers more accurate estimations than the traditional METRIC. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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22 pages, 615 KiB

Open AccessArticle

A Two-Echelon Inventory System with a Minimum Order Quantity Requirement

by Huaxiao Shen, Tian Tian and Han Zhu

Sustainability 2019, 11(18), 5059; https://0-doi-org.brum.beds.ac.uk/10.3390/su11185059 - 16 Sep 2019

Cited by 7 | Viewed by 3533

Abstract

In this paper, we study a two-echelon inventory system with one warehouse and multiple retailers, under the setting of periodic review and infinite horizon. In each period, retailers replenish their stocks from the warehouse, and the warehouse in turn replenishes from an external supplier. Particularly, as stipulated by the supplier, there is a minimum order quantity (MOQ) requirement for the warehouse. That is, the warehouse must order either none or at least as much as the MOQ. To investigate this system analytically, we assume retailers adopt the base-stock policy, and we design for the warehouse a new heuristic ordering policy, called refined base-stock policy, which conforms to the MOQ requirement. Moreover, in the case of shortages, we assume the warehouse adopts a virtual allocation policy, and therefore the orders for individual units are filled in the same order as the original demands at the retailers. To evaluate the long-run average system cost exactly, we present a position-based cost-accounting scheme, in which the cost associated with each unit is assigned to its first position at the warehouse. We also derive lower and upper bounds of the inventory parameters, facilitating the search for the optimal policy that minimizes the long-run average system cost. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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15 pages, 1233 KiB

Open AccessArticle

Inventory Model Design by Implementing New Parameters into the Deterministic Model Objective Function to Streamline Effectiveness Indicators of the Inventory Management

by Mária Stopková, Ondrej Stopka and Vladimír Ľupták

Sustainability 2019, 11(15), 4175; https://0-doi-org.brum.beds.ac.uk/10.3390/su11154175 - 02 Aug 2019

Cited by 14 | Viewed by 4643

Abstract

The aim of this article is to modify the parameters and thus the objective function of the deterministic model of inventory theory so that other important aspects, which influence inventory management, can be taken into consideration. These aspects include the nature of inventory consumption, the share of inventories in sales, the capacity of means of transport and, above all, the reliability of suppliers. This goal is achieved by performing sophisticated and specific calculations for the individual parameters in the modified model. The modification of the objective function of the deterministic model has created a new multi-criteria model. The outcome of this model sought to optimize the supply process in a way that minimizes the risks associated with a lack of inventories while maintaining the economic effectiveness thereof. The model effectiveness is examined by comparing the application of the deterministic model and the proposed model with modified objective function. The results of applying these individual models have been produced based on calculations of indicators showing inventory management effectiveness—the speed of inventory turnover and the average number of inventories in storage. Full article

(This article belongs to the Special Issue Inventory Management for Sustainable Industrial Operations)

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