Zero Inventory Research Articles

Lean Operations in Tertiary Institutions: A Tool for Elimination of Waste in Technical Universities, Ghana

Abstract
 The application of lean operation systems in tertiary institutions has a potential benefits to many universities in Ghana. The focus of this study was to systematical evaluate the basic principles of lean management and its application to tertiary institutions by streamlining structures and models that will provide satisfactory services for customers by eliminating administrative wastes. The survey design was used with questionnaire as the instrument for data gathering. A random sampling strategy was applied in obtaining the sample size for the study. The findings of the study revealed seven different types of administrative waste where each of these wastes were ranked in terms of their magnitude within the university. Also, the indication of the result is that, over staffing the number of academic or administrative units and underutilization of talent of employees’ were the most essential component of waste identified. Therefore, the techniques and tools to guide the implementation of lean model in the university as proposed by the study is to establish norms and standards; focus on the value of the customer; use punitive measures as deterrents; adhere strictly to budget lines; establish workflow sequence; ensure effective communication and information; zero inventory as well as follow laid down administrative procedures. The novelty of this study is that, it provides concrete direction in implementing lean frameworks in all universities and helps streamline activities that will create value by mapping the streams to satisfy the needs of the university community.

Two-level uncapacitated lot-sizing problem considering the financing cost of working capital requirement

During financial crisis, companies constantly need free cash flows to efficiently react to any uncertainty, thus ensuring solvency. Working capital requirement (WCR) has been recognized as a key factor for releasing tied up cash in companies. However, in literatures related to lot-sizing problem, WCR has only been studied in the single-level supply chain context. In this paper, we initially adopt WCR model for a multi-level case. A two-level (supplier-customer) model is established on the basis of the classic multi-level lot-sizing model integrated with WCR financing cost. To tackle this problem, we propose sequential and centralized approaches to solve the two-level case with a serial chain structure. The ZIO (Zero Inventory Ordering) property is further confirmed valid in both cases. This property allows us to establish a dynamic programming-based algorithm, which solves the problem in O(T4). Finally, numerical tests show differences in optimal plans obtained by both approaches and the influence of varying delays in payment on the WCR of both actors.

Towards Zero-Warehousing Smart Manufacturing from Zero-Inventory Just-In-Time production

Over the past half-century, manufacturers have strived to achieve “Zero Inventory (ZI)” manufacturing, which puts the burden on suppliers to build their warehouses nearby production lines to meet the strict time delivery requirements of ZI production. Considerable improvements in manufacturing processes have been made. However, this practice in the meanwhile brings excessive warehousing operations along the supply chain. Recently, massive up-front investment has been made by some larger manufacturers for industrial 4.0 and warehouse automation to facilitate warehousing operations, such as put away and picking. However, warehouse operation activities enhanced by automation are still non-value-adding and current practice of redundant handling process implies continuous cost increase with the demand expanding. Therefore, it is of significance to simplify the corresponding operations as much as possible. This paper makes a comprehensive introduction to a new manufacturing paradigm named Zero-Warehousing Smart Manufacturing (ZWSM) from the concept, practices, principles, and core technologies. ZWSM basically aims to avoid traditional non-value-adding warehousing operations such as put away and order picking, as well as to reduce the warehousing space for operations to the minimum. First, prototype layout and basic practices under ZWSM are proposed. Second, synchronization, unitization and uncertainty hedging, which are the key principles to achieve the ZWSM, are explicitly introduced. Third, A Zero-Warehousing Smart Manufacturing Platform (ZWSMP) is developed with the Internet of Things (IoT) enabled infrastructures. Corresponding logistics services are presented to provide information visibility and achieve operations improvement. A case study of the Hong Kong prefabrication construction project is used to demonstrate the materials delivery process among different supply chain partners to provide a basis for zero-warehousing achievement.

Analysis on Zero Inventory Management of New Energy Enterprises

The improvement of cost management and control of new energy enterprises is of great significance for realizing the harmonious coexistence between man and nature.The improvement of enterprise value is benefited from making full use of each cost input to obtain profits. Therefore, it is very important to find out the shortcomings in cost control and optimize it in time.“Zero inventory” is a cost-saving management model that many new energy companies have already implemented, or are exploring.The basic idea of “zero inventory” management is that the enterprise tends to zero the inventory of raw materials, products and finished products in the procurement, production and operation, to avoid the opportunity cost of inventory occupation, and to prevent inventory from being outdated as we ll as risks such as falling prices and damage.This paper takes the necessity of implementing zero inventory management in new energy enterprises as the starting point, analyzes the problems existing in the cost control of new energy enterprises, and puts forward some suggestions for improvement.

Heuristic algorithms for inventory replenishment with perishable products and multiple transportation modes

ABSTRACTThis study extends classic economic lot-sizing problems to permit the replenishment of age-dependent perishable inventories via multiple transportation modes. Inventory replenishment costs include a multiple-setup cost function that considers order setup, purchase, and cargo container costs. The objective is to identify the timing of orders, order quantities, and a choice from among I transportation modes that minimizes the cost of replenishing perishable inventories during a planning horizon of length T. We present a mixed-integer programming formulation of this problem and characterize properties of optimal solutions. We propose a primal-dual heuristic algorithm that runs in O(IT2). In addition, we provide heuristic algorithms for two special cases of the problem involving one or two replenishment modes. For the single replenishment mode problem, we propose (i) a dynamic programming algorithm that explores solutions that satisfy the Zero Inventory Ordering Policy and runs in O(T2) and (ii) a dynamic programming algorithm that explores solutions that satisfy the Less-than-Truckload first positioning property and runs in O(T3). For the two replenishment mode problem, we present a knapsack-based algorithm that identifies the minimum number of cargo containers required to meet demand. The running time of this algorithm is O(T2). We evaluate the quality of the solutions generated by these different approaches via extensive numerical analyses.

Offline Experiences and Value Creation in Omnichannel Retail

We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and test our thesis using data from a digital-first men’s apparel retailer and a pioneer of the so-called “Zero Inventory Store” (ZIS) format — a small footprint, experience-centric retail location which carries no inventory for immediate fulfillment, but fullfils orders via e-commerce. Using a risk-set matching approach, we calibrate our estimates on customers who are “treated”, i.e., have a ZIS experience, and matched with identical customers who shop online only. We find that post the ZIS experience, customers spend more, shop at a higher velocity, and are less likely to return items. The positive impact on returns is doubly virtuous as it is more pronounced for more tactile, higher-priced items, thus mitigating a key pain point of online retail. Furthermore, the ZIS shopping experience aids product discovery and brand attachment, causing sales to become more diffuse over a larger number of categories. Finally, we demonstrate that our results are robust to self-selection and potentially confounding effects of unobservable factors on the matched pairs of customers. Implications for retailing practice, including for legacy, offline-first retailers, are discussed.

Aggregate Production Planning, Casestudy in a Medium-sized Industry of the Rubber Production Line in Ecuador.

This research aims to improve the productivity in the rubber line of a medium-sized industry by increasing the production capacities through the use of the Aggregate Production Planning model. For this purpose an analysis of the production processes of the line was made and the aggregate plan was defined evaluating two strategies: Exact Production Plan (Zero Inventory) and Constant Workforce Plan (Vary Inventory) by studying the costs of both inventory maintenance and workforce. It was also determined how the installed capacity was used with the standards of the rubber line and measures for decreasing production costs were proposed. It was proven that only 70% of the plant capacity was being used so it could be possible to produce more units and to obtain a bigger market for the products of this line.+

Reflections on Zero Inventory from the Perspective of Supply Chain

This paper analyzes the present situation of zero inventory in manufacturing enterprises by analyzing the thoughts of zero inventory and its misunderstanding, and puts forward the reasonable inventory management concept. Enterprises should combine their own production and operation mode, scientific and reasonable to reduce inventory, not one-sided understanding or misunderstanding of the true meaning and role of zero inventory, not to blindly pursue zero inventory and simple imitation, copy the dogma, thus affecting the normal production operations. In this paper, from the perspective of supply chain management of zero inventory, inventory control by reasonable profit maximization for enterprises to provide theoretical support.

스마트공장을 위한 IT 융합 표준화 동향 분석과 시스템 구조

Smart factory requires 4 Zero factors including Zero Waiting-time, Zero Inventory, Zero Defect, Zero Down-time) that needs IT convergence for production resources of 4M1E(Man, Machine, Material, Method, Energy) in real time and event processing in all type of manufacturing enterprises. This paper will be explaining about core emerging production IT convergence technologies including cyber device security, 4M1E integration, real time event driven architecture, common platform of manufacturing standard applications, smart factory to-be model for small and medium manufacturing enterprises.

Experiments made for zero inventory control of essential drugs at public hospitals in Yuhuan county

The paper covered main practices made at public medical institutions in Yuhuan county,Zhejiang province in promoting zero inventory control of essential drugs.The experiments include better mechanism,building informationized settlement system of the entire drug flow,centralized drug purchase,as well as smart supply chain terminal execution system,and third-party payment.The zero inventory control has effectively cut back drug distribution.costs and achieved the all-win outcome of medical institutions and drug suppliers. Key words: Essential drug system; Primary healthcare institutions; Zero inventory; Drug distribution

Zero inventory and firm performance: a management paradigm revisited

According to the ‘zero inventory’ paradigm, inventory reflects waste and should be eliminated in order for performance to rise. In this study, we investigate the effect of inventory holding on firm performance, analysing 3057 firm years of data. Interpreting performance as a function of inventory, results show that firms with the lowest inventory have the worst performance (and vice versa). When understanding inventory as a function of performance, results indicate that low-performing firms carry the least inventory, whereas high-performing firms have the highest stocks. Besides questions of causality, our results do not support a paradigm which suggests that firms should move toward zero inventory.

Performance measurement and determination of optimal base stock level inventory system to improve the customer satisfaction in the Six Sigma environment

The main objective of this study was to measure the performances after implementation of innovative inventory management system in a stochastic environment and it was carried out in a casting company which currently implementing the Six Sigma concept towards achieving the product quality, on-time delivery and customer satisfaction at the least cost. Maintaining optimal inventory and forecasting future demand are not easy for the decision-maker of any enterprise. However, it is possible to strike a balance between the ideal zero inventory and the real-world avoidance of stock out costs through a minimum inventory system called base stock system. This study has examined the performance indicators and investigations have been undertaken to assess the effectiveness and efficiency of the implementation of the Six Sigma system. This paper proposes a generalised approach for determining the optimal base stock level to forecast stochastic demand and improve the on-time delivery and in turn, improve the efficiency of the process.

The Analysis of Zero Inventory Drift Variants Based on Simple and General Order-Up-To Policies

In this paper, simple and general Order-Up-To (OUT) models with Minimum Mean Square Error (MMSE) forecast for the AR(1) demand pattern are introduced in the control engineering perspective. Important insights about lead-time misidentification are derived from the analysis of variance discrepancy. By applying the Final Value Theorem (FVI), a final value offset (i.e., inventory drift) is proved to exist and can be measured even though the actual lead-time is known. In this regard, to eliminate the inherent offset and keep the system variances acceptable, two kinds of zero inventory drift variants based on the general OUT model are presented. The analysis of variance amplification suggests lead-times should always be estimated conservatively in variant models. The stability conditions for zero inventory drift variants are evaluated in succession and some valuable attributes of the new variants are illustrated via spreadsheet simulation under the assumption that lead-time misidentification is inevitable.

An efficient approach for solving the lot-sizing problem with time-varying storage capacities

We address the dynamic lot size problem assuming time-varying storage capacities. The planning horizon is divided into T periods and stockouts are not allowed. Moreover, for each period, we consider a setup cost, a holding unit cost and a production/ordering unit cost, which can vary through the planning horizon. Although this model can be solved using O( T 3) algorithms already introduced in the specialized literature, we show that under this cost structure an optimal solution can be obtained in O( T log T) time. In addition, we show that when production/ordering unit costs are assumed to be constant (i.e., the Wagner–Whitin case), there exists an optimal plan satisfying the Zero Inventory Ordering (ZIO) property.

The cost of lead-time variability: The case of the exponential distribution

We present closed-form solutions for the reorder point, z, the order quantity with non-zero lead time, Q, and the total relevant cost, TRC(z,Q,K′), where the lead time is doubly truncated (at r=z/D and r+q=z/D+Q/D, D being a constant demand rate), using the concept of pseudo-setup cost, K′. We aim to provide a paradigm for quantifying the effect lead-time variability on cost, as such paradigms are lacking in the inventory literature. From our analysis, we conclude that to achieve zero inventory (ZI) in a stochastic lead-time setting, both the setup cost and the lead-time variability would have to be eliminated. Furthermore, it is the variance and not the mean that affects the total relevant cost in a stochastic lead-time model. Besides the statistical analysis, we examine the economic impact of the truncation and determine model accuracy by means of a heuristic that is robust to parameter changes and that allows the convenience of substituting in the analysis the doubly truncated Exp(λ) by an untruncated Exp(λ+1), with a loss of accuracy of no more than 5 percent for all numerical examples tested.

Probabilistic Analyses and Practical Algorithms for Inventory-Routing Models

We consider a distribution system consisting of a single warehouse and many geographically dispersed retailers. Each retailer faces demands for a single item which arise at a deterministic, retailer specific rate. The retailers' stock is replenished by a fleet of vehicles of limited capacity, departing and returning to the warehouse and combining deliveries into efficient routes. The cost of any given route consists of a fixed component and a component which is proportional with the total distance driven. Inventory costs are proportional with the stock levels. The objective is to identify a combined inventory policy and a routing strategy minimizing system-wide infinite horizon costs. We characterize the asymptotic effectiveness of the class of so-called Fixed Partition policies and those employing Zero Inventory Ordering. We provide worst case as well as probabilistic bounds under a variety of probabilistic assumptions. This insight is used to construct a very effective algorithm resulting in a Fixed Partition policy which is asymptotically optimal within its class. Computational results show that the algorithm is very effective on a set of randomly generated problems.

A conceptual framework for the implementation of Zero Inventory and Just-In-Time manufacturing concepts

This article deals with major issues of implementing Zero Inventory (ZI) and Just-In-Time Production (JIT) concepts. These concepts most likely reduce the waste in terms of reduction in inventory and scrap levels for improving productivity and quality in manufacturing organizations. Firstly, a review on the implementation of ZI/JIT has been presented to critically evaluate the major issues. Secondly, the major implementation issues of ZI and JIT have been discussed with help of a conceptual model. Thirdly, behavioral and cultural characteristics of firms have been discussed with reference to the implementation of ZI and JIT. Finally, the model has been applied to Finnish firms to discuss the various issues involved in the implementation of ZI and JIT. © 1998 John Wiley & Sons, Inc.

A conceptual framework for the implementation of Zero Inventory and Just‐In‐Time manufacturing concepts

A conceptual framework for the implementation of Zero Inventory and Just‐In‐Time manufacturing concepts

From Wagner-Whitin's dynamic lot size model towards zero inventory

This article discusses the interface between zero inventory (ZI) and the dynamic lot size problem. The conventional Wagner-Whitin dynamic lot size model shows a good ffi computational e ciency when obtaining the optimal lot-sizing policy, but it ignores reduction of lot size and total cost. The 'zero inventory' philosophy strives for the goals of zero inventory at the end of each period and minimum total cost. The setup cost is fixed in the Wagner-Whitin model, but is considered as a parameter in zero inventory (ZI) philosophy: in general, the setup cost is treated as a policy variable in ZI. Zangwill examined the case of stationary setup cost reduction, but did not discuss the case of nonstationary setup cost reduction. This paper presents a new expression for total setup cost and total holding cost for the Wagner-Whitin model. By adopting this new expression, we obtain a sufficient and necessary con dition such that ZI is the optimal policy in the Wagner-Whitin model. Regardless of whether the setup cost reduction is stationary or nonstationary, the total setup cost reduction over all periods increases when the amount of setup cost reduction increases. This result suggests that the optimal policy for the Wagner-Whitin model is close to ZI. Most presentations of ZI have been descriptive with very few mathematical models. This paper seeks to demonstrate by a mathematical approach that reducing the setup cost can make the Wagner-Whitin model approach ZI.

The effects of varying set‐up costs

The concept of zero inventory (ZI) is a powerful tool to improve production economics. The major factor in ZI is set‐up cost reduction. Examines what will happen when set‐up costs are stationarily and non‐stationarily reduced by mathematical presentations and simulation. The results are useful for real practice. Zangwill observes that reducing set‐up costs need not decrease inventory by a special example of non‐stationary cases. Likewise, set‐up cost reduction need not decrease total production and inventory costs. By using simulation, obtains results contrary to Zangwill. Most presentations of set‐up cost reduction consider the stationary case. It is hard to find the degree of cost variations by mathematical models. Thus uses a mathematical approach and a few simulation results that varying set‐up costs are provided. Reduces set‐up costs stationarily and non‐stationarily to examine the effects on total costs and total holding costs.