Inventory Control and Big Data

Author(s):  
Meghna Sharma ◽  
Niharika Garg

This chapter provides the relation between automated inventory control and generation of big data using the process. Conversion from manual to automated inventory process leads to generation and management of too much data. Possible boons and banes of the conversion of inventory control system to automated one are discussed in detail. In the initial sections explanation about inventory control and benefits of automating is given. Then overall architecture of big data and its management is discussed .Finally, tradeoff between the usage of automated inventory control system with its benefits and generation of too much data and handling it, is discussed.

Big Data ◽  
2016 ◽  
pp. 1543-1554
Author(s):  
Meghna Sharma ◽  
Niharika Garg

This chapter provides the relation between automated inventory control and generation of big data using the process. Conversion from manual to automated inventory process leads to generation and management of too much data. Possible boons and banes of the conversion of inventory control system to automated one are discussed in detail. In the initial sections explanation about inventory control and benefits of automating is given. Then overall architecture of big data and its management is discussed .Finally, tradeoff between the usage of automated inventory control system with its benefits and generation of too much data and handling it, is discussed.


Author(s):  
Gustavo Poot Tah ◽  
Erika Llanes Castro ◽  
José Luis López Martínez ◽  
Victor Chi Pech

This paper presents the design and development of a mobile application that uses QR codes for the inventory control of a computer center. This application was developed to support the administration of the computer center of the Multidisciplinary Unit Tizimin, with the aim to reduce costs and time of searching for articles when making an inventory, by leveraging the capabilities of smartphones and tablets. The implementation of the system was carried out using free software.


IJAcc ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 132-139
Author(s):  
Erna Astriyani ◽  
Desy Apriani ◽  
Meri Mayang Sari

The system that is currently running in recording inventory at PT Berlina Tbk Tangerang is considered ineffective and efficient because it still uses paper and the process of inputting and recapping goods data is semi-computerized in Microsoft Excel. which causes problems, namely too much stock of goods so that it increases the load in the warehouse and too little stock of goods which results in an exhaustion of stock in the warehouse. To solve this problem, we need an inventory control information system. The method of analysis uses the EOQ (Economic Order Quantity) method. For the system design process using sublime as the writing language and programming PHP, and XAMPP as localhost, the database uses MySQL. This study aims to design an inventory control system in the HRD department at PT Berlina Tbk Tangerang, and to make it easier for the HRD Department to input and create inventory reports. With this research, it can produce an inventory control system design that is more effective and efficient and can find out the storage costs in the warehouse. From the calculation of the EOQ method, it is found that it is 20% smaller than the previous storage and the total cost of ordering in a year is 2x orders. Thus, it means that there is a very real difference between the inventory policies implemented by the company and the EOQ method.


2018 ◽  
Vol 13 (4) ◽  
pp. 1037-1056 ◽  
Author(s):  
Huthaifa AL-Khazraji ◽  
Colin Cole ◽  
William Guo

Purpose This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.


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