This document evaluates reorder point and min-max planning methods used in Oracle Applications Release 10.7 from the perspective of a non-manufacturing environment. It outlines the key assumptions and limitations of these traditional approaches, such as treating items independently and assuming stable demand. More advanced concepts like distribution requirements planning and just-in-time delivery are presented as alternatives.
To understand following features:
OPM Inventory conversion.
Material traceability: Enhanced material control
Dual UOM functionality.
Material Status control.
Advanced Lot control.
Lot indivisibility functionality.
Material aging workflow.
To understand following features:
OPM Inventory conversion.
Material traceability: Enhanced material control
Dual UOM functionality.
Material Status control.
Advanced Lot control.
Lot indivisibility functionality.
Material aging workflow.
Oracle iProcurement is a self service based requisitioning application that controls employee purchasing. It is a key component of oracle advanced procurement, the integrated suite that dramatically cuts all the supply chain management costs. The Oracle iProcurement functionality provides the essentials for the ordering portion of the procurement process. This includes catalog content management, requisitioning, purchase order creation, and receiving orders. This webinar will deal in brief about the benefits and usages of Oracle iProcurement.
Agenda:
- Procurement process: Oracle iProcurement
- Indirect and Direct Sourcing
- Why are we switching to iProcurement?
- Various Benefits
- Oracle iProcurement Release 12 Enhancements
- Oracle iProcurement Overview
- Oracle iProcurement in Comprehensive Procure-to-Pay Flow
- Core Features of Oracle iProcurement
- Oracle Service Procurement Integration
Oracle iProcurement is a self service based requisitioning application that controls employee purchasing. It is a key component of oracle advanced procurement, the integrated suite that dramatically cuts all the supply chain management costs. The Oracle iProcurement functionality provides the essentials for the ordering portion of the procurement process. This includes catalog content management, requisitioning, purchase order creation, and receiving orders. This webinar will deal in brief about the benefits and usages of Oracle iProcurement.
Agenda:
- Procurement process: Oracle iProcurement
- Indirect and Direct Sourcing
- Why are we switching to iProcurement?
- Various Benefits
- Oracle iProcurement Release 12 Enhancements
- Oracle iProcurement Overview
- Oracle iProcurement in Comprehensive Procure-to-Pay Flow
- Core Features of Oracle iProcurement
- Oracle Service Procurement Integration
A New Framework for Safety Stock ManagementCognizant
A methodology for computing how much safety stock, or buffer stock, of inventory a vendor should carry, taking into consideration lead times, reorder points, stock-out risks, demand, forecast errors, the supply chain and other safety stock management factors.
An analysis of what are the challenges faced by companies in managing their suppliers/vendors.
Bit Wave Solutions has developed iSupplier Portal to overcome those challenges and streamline procurement process effectively.
During this webcast you will learn:
* E-Business Suite allows budgets to be managed in the same way as normal transactions, for each unique combination of your Chart of Accounts.
* Use summary accounts or rollup groups to manage and maintain.
* General Ledger gives you a variety of tools to create, maintain, and track your budgets, including the ability to upload budget amounts from your spreadsheet software.
Agenda:
- Understand Budget Accounting Cycle
- Use Various Budget Methods
- Budgets and Budgets Organizations
- Manual Budgets
- Effective use of Budget Upload Via Web ADI
- Create Budgets and Maintain Budgets
- Review and correct budgets
- Freeze Budgets
- Reports on budgets
- Q & A Session
Safety stock (also called buffer stock) is a term used by logisticians to describe a level of extra stock that is maintained to mitigate risk of stockouts due to uncertainties in supply and demand
Safety stock is an additional quantity of an item held in the inventory in order to reduce the risk that the item will be out of stock, safety stock act as a buffer stock in case the sales are greater than planned and or the supplier is unable to deliver the additional units at the expected time
Lecture 3 Time varying demand inventory models.pdfChristina272851
it is i Illustrate the use of your program for the following example involving 20 items:
c. What percentage of the total dollar usage is contributed by the top 20% of the items
and by the bottom 50% of the items.
Illustrate the use of your program for the following example involving 20 items:
c. What percentage of the total dollar usage is contributed by the top 20% of the items
and by the bottom 50% of the items.
Illustrate the use of your program for the following example involving 20 items:
c. What percentage of the total dollar usage is contributed by the top 20% of the items
and by the bottom 50% of the items.
Chapter 12 - Inventory Management
Chapter 13 - Inventory Management
Chapter 13
Inventory ManagementTeaching Notes
This is a fairly long and important chapter. Important points are:
1.Good inventory management is important for successful organizations.
2.The key inventory management issues are when to order and how much to order.
3.Because all items are not of equal importance, it is necessary to establish a classification system for allocating resources for inventory control.
4.EOQ models answer the question of how much to order. Variations of the basic EOQ model include the quantity discount model and the economic production quantity (EPQ) model.
5.EOQ models tend to be rather robust: even though one or more of the parameters may be only roughly correct, the model can yield a total cost that is close to the actual minimum.
6.ROP models are used to answer the question of when to order. Different models are used, depending on whether demand, lead time, or both are variable.
7.Other models described are the fixed interval model and the single-period model.
8.All of the models in this chapter pertain to independent demand.
The single-period model is used to handle ordering of perishables (e.g., fresh fruits and vegetables, seafood, and cut flowers) as well as items that have a limited useful life (e.g., newspapers and magazines). Analysis of single-period situations generally focuses on two costs: shortage and excess. Shortage costs may include a charge for loss of customer goodwill as well as the opportunity cost of lost sales or unrealized profit per unit. Excess cost pertains to items left over at the end of the period and is the difference between purchase cost and salvage value. There may be costs associated with disposing of excess items, which would make the salvage value negative and hence increase the excess cost per unit.
Answers to Discussion and Review Questions
1.Inventories are held: (1) to meet anticipated customer demand, (2) to smooth production requirements, (3) to decouple operations, (4) to reduce the risk of stockouts, (5) to take advantage of order cycles, (6) to hedge against price increases, (7) to permit operations, and (8) to take advantage of quantity discounts.
2.Effective inventory management requires: (1) a system to keep track of inventory on hand and on order, (2) a reliable forecast of demand that includes an indication of possible forecast error, (3) knowledge of lead times and lead time variability, (4) reasonable estimates of inventory holding costs, ordering costs, and shortage costs, and (5) a classification system for inventory items.
3.The four costs associated with inventories include the following:
(1)Purchase cost – Amount paid to a vendor or supplier to buy the inventory.
(2)Carrying or holding costs – Cost of physically having items in storage. Costs include interest, insurance, taxes, depreciation, picking, and warehousing costs (heat, light, rent, and security).
(3)Ordering costs – Cost of ordering ...
Inventory Control and Replacement Analysis Priyanshu
Hello Everyone!
This is the best ppt on 'Inventory Control and Replacement Analysis' that you can ever find.
I tried to include all the topics that will make the reader to grasp everything quickly.
These notes are also helpful for students for their university exams.
Go through the entire ppt and let me know your feedback in the comment box.
Learn and Enjoy!
Thank You!
Defination : Inventories constitute an important component of a firms working capital .The various features of inventory are inventory as current asssets ,level of liquidity and liquidity lags .
Purpose : The purpose of holding inventoryis to achieve efficiency through cost reduction, increased sales volume ,to avail quantity discounts ,reduce risk of production stoppages ,reducing ordering costs and time .
Inventory Management techniques : 2 types :
1. Economic order quantity : it is the order quantity that minimisesthe total cost associated with inventory management .
2. 2. ABC system : A – items of high value but small in number
B – items of moderate value and size require reasonable attention
C - items of smaller value
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Minimax vs reorder point
1. Oracle Reorder Point and Min-max Planning: Based on Outdated Concepts?
Dr. Volker Thormählen
0 Summary
The Inventory module of Oracle Applications Release 10.7 supports only 2 planning methods
for independent demand: Reorder Point and Min-max planning. In the following both
methods are evaluated from the viewpoint of a non-manufacturing (importer, wholesaler,
distributor, retailer, etc.) environment. The functional limitations of such traditional
approaches will be explained and compared with more progressive or trendy concepts such
as Distribution Requirements Planning and Just-In-Time delivery. Kanban replenishment, a
new functionality in Release 11, is not covered, because it is mainly a means of supporting
pull-based inventory replenishment in manufacturing systems.
1 Reorder Point Planning
Reorder Point planning and its derivatives have been around since 1934, see [4], p. 40. A
continuous review of inventories is always assumed. A fixed order quantity is usually
suggested by the system whenever the inventory position drops to the reorder point or lower.
Note that the inventory position includes on-hand and on-order stock (= planned receipts).
The Reorder Point (also known as reorder level) is equal to the safety stock plus the
expected average sales (or usage) quantity within the replenishment lead time. From a
physical standpoint, these two types of inventory levels are not separated. Safety stock, also
referred to as buffer stock, is used to protect against the random fluctuations in demand
and/or supply. It makes up inventory held to protect against forecast errors, changes in
customer's orders, quality defects, or late shipments from the supplier of an inventory item. A
graphical illustration (the traditional saw-tooth diagram) and a mathematical treatment of the
system and its derivatives are provided in [7].
Reorder Point planning is equivalent to a common visual review system called two-bin
system. This method uses two physical storage locations with stock of the same item. When
one bin becomes empty, a replenishment order is placed to refill it while demand is filled from
the second bin.
Reorder Point planning regards replenishment quantity as the main cost driver. But
frequently the number of purchase order lines during the planning horizon is considered to be
a more appropriate measure for cost behaviour, see [8], p. 87. Other weak points are related
to rather strict assumptions needed to derive the basic mathematical model(s) for Reorder
Point planning. The standard assumptions for Reorder Point planning are listed in the
following:
• Inventory items are treated entirely independent of others, that is, possible benefits from
joint reorder planning (as described in section 3, see below) are ignored or do not exist
• Planning horizon is rather long, usually 1 year
• Total sales (or usage) during the planning horizon is constant
• Demand rate is deterministic with constant mean and stable variability, that is, the item is
in the mature stage of its life cycle
• Total demand can be fully covered, that is, no shortages are allowed
• Replenishment lead time is constant, that is, of zero or nonzero duration
• Inventory carrying costs per unit per year do not depend on the replenishment quantity,
that is, semi-variable or semi-fixed (= stepped) costs do not occur by definition
• Acquisition cost per unit does not depend on order quantity, that is, quantity discounts for
larger orders on unit purchase price and/or unit transportation cost are neglected
• Withdrawals from inventory take place in rather small quantities, that is, crossing of the
Reorder Point can be recognised in time
• Purchase orders for inventory replenishment can be issued at any time, that is, no time
and no quantity restrictions exist with respect to the reorder quantity
page 1 of 9
2. • The (suggested) purchase order quantity need not be an integer number of units, that is,
there are no upper or lower limits as well as rounding rules on its size
• The entire purchase order quantity is delivered at the same time, that is, no partial
shipments are allowed
• Permanent monitoring of the Reorder Point is mandatory , that is, a continuous stock-
taking sub-system is required in practice for a continuous review system with or without
manual override capability with respect to reorder quantity
Most of the standard assumptions listed above are also relevant for Oracle Reorder Point
planning, but are not explicitly and completely mentioned in corresponding Inventory
Reference Manual, see [5]. Knowing them precisely makes the assessment of applicability
much easier for special categories of inventory items, for example:
• perishable, exquisite, style, and fashion items
• items with rapidly changing demand rate
• items subject to volume discounts and freight restrictions
• new and discontinued items
• extremely seasonal items
• high-value items
• damaged, obsolete, used and otherwise deteriorated items
• rare items which are difficult to replace
• heavy and bulky items (where drop-shipment is frequently more cost-effective than
stocking; besides, drop-shipment of sales orders is a new function in Release 11.)
Oracle Reorder Point planning is intentionally not a completely automated system which
allows no human intervention. It is generating replenishment proposals referred to as
purchase requisitions using the so-called Economic Order Quantity (usually abbreviated as
EOQ) and the safety stock as central inventory control parameters. Oracle offers only 3
options for calculation of safety stock for each item, see [5], p. 9-282:
• Manually entered safety stock quantities and the date for which each quantity is effective
• Percentage of forecasted demand for the item
• Service level and MAD. Service level represents the probability that a customer order can
be filled from available inventory. MAD represents the mean absolute deviation of
forecast errors. Safety stock quantity is calculated using an equation based on described
input parameters.
Decision on safety stock is important, because in large measure, safety stock determines
customer service level and total inventory investment. The more difficult an item is to predict,
the more safety stock is allocated through Reorder Point logic. Since most forecast errors
occur in slow-moving items, an inventory policy that bases safety stock on forecast error is
wrong, see [8], p. 75. Allocating a fixed total safety stock investment among all items of an
assortment to minimise
• either expected total stockout occasions per year
• or expected total value of shortages per year
are much smarter strategies, see [7], p. 246. Such aggregate considerations in fact devalue
the concept of the Reorder Point planning with safety stock calculated for individual items.
Oracle Reorder Point planning uses inventory forecasting information to calculate average
demand. Two naive forecasting methods are available based on historical item usage:
Statistical forecasting and Focus forecasting, see [5], p. 9-297, also [8] and [9].
Oracle Reorder Point planning creates purchase requisitions for all items that meet the
reorder condition optionally constrained by minimum and maximum order quantities as well
as a fixed lot size multiplier, see [5], p. 9-285.
page 2 of 9
3. Oracle Reorder Point planning calculates the Reorder Point (comprising safety stock)
independent of EOQ, although efficient algorithms have been published for simultaneous
calculation of both decision variables, for example see [6], p. 728 and [10], p. 291.
Simultaneous calculation usually results in lower total cost in a pre-specified planning
horizon.
Oracle Reorder Point planning does not consider possible price breaks and volume freight
discounts when calculating the EOQ.
Oracle Reorder Point planning is based on the assumption that replenishment lead time is
constant. More advanced models treat replenishment lead time as a probabilistic variable
following a normal, gamma, uniform, or other distribution. Generally a more realistic Reorder
Point quantity will be achieved.
When Oracle Reorder Point planning is used to calculate purchase requisitions, open
customer orders are ignored. You could run corresponding planning report and miss items of
which you have insufficient quantity to cover an open customer order. If the inventory
position is not below Reorder Point, the item will not appear on the planning report at all. You
can also have an item with an inventory position below the order point, and a large open
sales order, but the suggested fixed order quantity is only sufficient to cover the independent
demand forecast. If you convert these suggested quantities directly into purchase
requisitions you will again be short, see [1], p. 2.
Another problem inherent in Oracle Reorder Point planning is related to visibility and
comprehensibility. There are no Reorder Point or order quantity levels visible in the system
anywhere. You must run the corresponding planning report to see these levels. At the same
time, suggested order quantities are not exactly reproducible, see [1], p 2.
2 Min-max Planning
Besides Reorder Point planning Oracle Inventory covers Min-max planning. This approach
again assumes continuous review of inventory levels. It is a planning method where the
minimum is the reorder point and the maximum is the level the inventory is not to exceed.
Order quantity is variable and is calculated by subtracting the inventory position (= on-hand
quantity plus on-order quantity) from the maximum inventory level. When the result falls
below the minimum quantity a reorder quantity up to maximum stock is suggested. The
corresponding lot-sizing method is usually called replenishment to maximum stock.
The Min-max system is commonly used for low volume items (so-called "C" parts of an ABC
inventory analysis). The main advantage of this system is its simplicity. A possible
disadvantage is the variable order quantity. A graphical illustration and a mathematical
treatment of the Min-max system and its derivatives are provided in [7].
In case of unit-sized withdrawals from stock, Reorder Point and Min-max planning are
equivalent, that is, resulting in the same reorder quantity. Most of the standard assumptions
for continuous review inventory systems therefore also apply to Min-Max planning, see
section 1.
Oracle Min-Max planning does not take into account forecast demand during replenishment
lead time when calculating the replenishment quantity, see [5], p. 9-280.
Oracle Min-Max replenishment quantity recommendations take order modifiers into account.
This may change the initial order size calculated by the system , see [5], p. 9-280.
The major problem with present Oracle Min-max planning is that the minimum and maximum
levels must be maintained manually by the users, see [1], p 1. This is very labour intensive
when planning comprises many independent demand items and the system cannot react
page 3 of 9
4. effectively to changing conditions. To counteract this, inventory managers may tend to
maintain high minimum quantities to cover random usage fluctuations. Errors in the levels
are often not discovered until the inventory is dangerously low or until a physical count (or
cycle count) reveals inventory in excess. This type of manually maintained system is not at
all acceptable from both, a manufacturing and non-manufacturing point of view.
3 Periodic Review System
In a periodic review system derivative usually called Topping-up system every T units of time
a replenishment order is placed to raise the inventory position to the order-up-to-level S. The
value of T is usually pre-specified and often dictated by external factors, such as frequency
of full truckload shipment opportunities. The order-up-to-level S must be sufficient to cover
demand through a disposition period of duration T + L. Figure 1 shows essential details of
the Topping-up system.
fixed reorder cycle: T1 = T2 = T3 = T4
variable order quantity: R1 # R2 # R3 # R4
quantity
S = maximum quantity
R1 R2 R3 R4
variable order quantity
L
L L remaining quantity
T1 T2 T3 T4 time
review review review review
T = constant review interval
L = constant replenishment lead time
order quantity = maximum quantity - remaining quantity
Figure 1: Periodic Review System: Illustration of the Topping-up System
The amount of safety stock carried for an inventory item in a periodic review system depends
on the variability of demand (forecast error) and the desired level of one-time shipments.
The Topping-up system is used rather frequently in trading businesses where relatively short
delivery times can be achieved by means of co-ordinated replenishment from a central
distribution warehouse. The main disadvantage of the Topping-up system is that the
inventory carrying costs are higher than in comparable continuous review systems.
Presently Oracle Inventory does not support any periodic review system (also called fixed
reorder cycle system) and corresponding derivatives such as the briefly described Topping-
up system.
4 Joint Reorder Planning
Joint replenishment usually happens when items kept in the same inventory are ordered from
one supplier. A joint purchase order comprises several inventory items to obtain volume
page 4 of 9
5. and/or transportation discounts. Some of the benefits achieved from joint replenishment of
purchased inventory items in these situations are listed in below:
• Transportation economies (for example, full truck load shipments)
• Reduced costs for sending purchase orders to suppliers
• Trade discounts based on order value and/or order quantity
• Accounts payables efficiencies achieved through reduction in paperwork
For manufactured items analogous benefits can be achieved.
A prerequisite for joint reorder planning is a periodic review system, see previous section.
Corresponding inventory approach places purchase orders on a predetermined time
schedule (daily, weekly, monthly, etc.). The actual purchase order quantity will vary from
order to order based on how many units have been issued.
At present Oracle Inventory does not support replenishment planning methods based on
periodic review of inventory levels, although joint reorder planning is an attractive approach
for some trading businesses.
5 Combination of continuous and periodic review system
Combining the logic of Reorder Point planning with the logic of a periodic review system is
possible in theory and practice. In addition to cyclic reordering, such a system will
automatically generate a replenishment proposal as soon as the inventory position falls
below the Reorder Point level. If this happens the system calculates the interval that starts
from the point in time that the inventory position falls below the Reorder Point up to the
availability date of the next regular planning run. This is used for the net requirements
calculation. Suggested purchase order quantity must cover this time span. At the following
regular planning date corresponding item is planned as usual.
It has been shown that, under fairly general assumptions concerning demand pattern and
cost factors involved, the described system produces lower total costs than any other.
However, the computational effort to obtain the best values of the three inventory control
parameters,
• minimum stock level,
• maximum stock level, and
• review time
is more intense, see [7], p. 241. The system is therefore most suitable for so-called "A" items
of an ABC inventory analysis.
Oracle Inventory does not support a combination of continuous and periodic replenishment
planning for independent demand. Some competitive business software packages have this
capability, for example SAP R/3.
6 Time-Phased Order Point Planning
This approach has been derived from well-known Material Requirements Planning (MRP)
logic as a means to determine when inventory replenishment orders must be placed to
ensure a continuous supply of goods.
Scheduled customer orders, demand forecasts or a combination of both are used to
determine gross requirements at regular intervals for an item. Gross requirements represent
the total demand for an item prior to accounting for corresponding quantity on hand and
quantity on order (= scheduled to be received). The period split (day, week, month, etc.) for
schedules and/or forecasts and the number of periods included in the schedules and/or
forecasts is usually specified individually for each item, in other words, periods to be
considered during requirements planning are determined by the user. The gross
page 5 of 9
6. requirements quantities are used in the planning process to calculate net requirements for
every period as follows:
• Gross requirements
• minus projected available on hand inventory (= quantity physically in stock)
• plus scheduled receipts (= orders released to supply sources in a prior planning period)
• equals net requirement
When there is a net requirement, then an order proposal is generated. The quantity stated in
the order recommendation is calculated by the system according to a predetermined lot-
sizing method. Depending on the method selected several net requirements quantities are
pooled into one order quantity.
The replenishment lead-time offset is established by determining when an item is needed to
satisfy a net requirement. This allows the system to schedule a planned order receipt in one
time period and the planned order release in a prior time period. The time span between
these two dates is the required lead time. Therefore, a planned order release includes a
release date and a due date. The planned order release results in one or more purchase
orders which are transmitted to suppliers. Of course, a supplier can only ship the ordered
quantity punctually if he gets corresponding purchase order on time. Planned replenishment
orders exist only within the system and can be modified or cancelled during subsequent
planning runs if conditions change.
A simple numerical example for time-phased order point planning is shown below using the
constants and variables listed in table 1.
Symbol Meaning Dimension Value
Variables
t actual actual coverage date business calendar date to be calculated
t planned planned coverage date business calendar date to be calculated
t arrival requested arrival date business calendar date to be calculated
Constants
t calendar present planning date business calendar date 100
T period length of planning period workdays 10
T delivery delivery lead time workdays 25
T inspection incoming goods inspection time workdays 10
T safety safety stock time workdays 5
Table 1: Meaning of symbols, variables, and given parameters for coverage calculation
10 workdays per planning period are assumed, see table 1. Available stock covers 4,5
periods, see table 2. Consequently 45 workdays are covered. Present date of the business
calendar equals 100. Accordingly actual range of coverage date equals 100 + 45, that is,
tactual = 145.
planning period P1 P2 P3 P4 P5
projected available 1500 1200 1000 700 200
- forecast demand 300 200 300 500 400
= net requirements 1200 1000 700 200 -200
Table 2: Relevant quantities subdivided by planning periods
Expected total replenishment lead time equals 50 workdays, see table 1. Accordingly
planned range of coverage date equals 100 + 50, that is, tplanned = 150, see table 3.
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7. t calendar + T period + T delivery + T inspection + T safety = t planned
100 + 10 + 25 + 10 +5 = 150
Table 3: Formula for calculation of t planned
If tactual < tplanned a purchase order must be issued. This reorder condition is met because 145
< 150. Requested arrival date tarrival for the purchase order is calculated as follows:
t actual - T inspection - T safety = t arrival
145 - 10 -5 = 130
Table 4: Formula for calculation of t arrival
Hence time-phased order point planning is a method that schedules each independent
demand item to arrive at the proper point in time (that is, Just-In-Time) at the warehouse.
Order size is determined by making use of an appropriate lot-sizing method, for example
periods of supply. This method establishes, primarily through experience, an order quantity
that will cover a pre-specified period of time. Thus EOQ calculation can be replaced by
shipments totalling multiple periods of actual and/or forecasted demand.
Presently Oracle Inventory does not support time-phased order point planning. This in turn
means, that time-phased inventory planning can not be combined with dynamic lot-sizing
methods such as the following:
• periods of supply
• period order quantity
• lot-for-lot
• part period balancing
• least unit cost
• least total cost
Lot-sizing methods for individual items with time-varying demand are further detailed in [7], p.
198.
7 Distribution Requirements Planning
Time-phased order point planning is closely related to Distribution Requirements Planning
(DRP). In the mid seventies this planning method appeared on the scene to assist with
problems related to physical distribution, see [4], p. 41. DRP involves meeting customer
requirements and receiving and storing goods at the lowest cost possible for a pre-specified
planning horizon.
Distribution Resource Planning is a scheduling system that extends DRP into the planning of
key resources contained in a distribution system such as warehouse space, warehouse
workforce, investment into inventory, and transportation capacity.
Distribution systems are usually classified as being either a push or a pull system. A push
system moves the inventory from a central source of supply out to the field warehouses.
Thus replenishment decisions are made centrally, based on forecasted and/or actual
demand. This is in contrast to a pull system where replenishment decisions are made at the
field warehouses. DRP is most frequently used in conjunction with a push system of
distribution inventory planning and control where all levels of the distribution system are
owned by the same company.
A significant number of trading companies who serve customers through a distribution
network have substituted Reorder Point respectively Min-max planning in favour of DRP
where emphasis is on order timing and quantity methods.
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8. Oracle Inventory is suitable for representation of a company's inventory sites and business
units as well as corresponding physical and logical units. In other words, definition of
distribution structures can be defined without considerable restrictions. This is also true for
inter-inventory transfer transactions within a distribution network.
• DRP (as needed for a push distribution system) is presently not completely available
within the functional scope of the Oracle Inventory module.
• Oracle Reorder Point or Min-max inventory planning can be utilised for the purpose of a
pull distribution system. But small customisations may be necessary for particular
distribution networks, see practical case study outlined in [1].
8 Conclusions
From the perspective of trading businesses continuous review systems such as Oracle
Reorder Point and Min-max planning are not old-fashioned. But their successful application
heavily depends on the goodness of fit between the inventory planning model (and its
underlying assumptions) on the one side and business reality on the other. For particular
inventory item categories and non-linear cost behaviour (due to price breaks, freight
restrictions, and the like) derivatives of the basic planning models are desirable.
Oracle Inventory does not support a wide choice of inventory planning models for
independent demand. The ones available deserve some enhancements. The choice of lot-
sizing methods is limited to EOQ and replenishment up to maximum stock level. But as more
models and methods can be selected the approximation to business reality will improve.
More progressive or trendy concepts suitable for distribution inventory planning and
distribution channel integration (frequently referred to as inter-corporate logistics, quick
response, continuous replenishment, supply chain management, partnership in merchandise
flow, just-in-time distribution, and stockless materials management) are not an integral part of
Oracle Inventory Release 10.7.
9 Remark
No claim concerning the completeness and correctness of the statements in this article can
be made. They represent purely the author’s own understanding of Oracle Inventory
Release 10.7.
Several people contributed to this article in various ways. These include Russel Hougthon,
Stephan Seltmann, and Ian D. Spencer. To them all go my heartfelt thanks.
10 Bibliography
[1] Fink, John, Planning - MinMax or Reorder Point. Is there another option?, Presentation
and Abstract, OAUG fall conference, Sept. 26-30, 1999, Orlando, Florida, 198 slides, 10
pages
[2] Graham, Gordon, Distribution Inventory Management, Inventory Management Press,
Richardson, Texas, 1988, 336 pages, ISBN: 0-31-701548-6
[3] Harmon, Roy L., Reinventing the Warehouse: World Class Distribution Logistics, The
Free Press, New York, etc. 1993, 364 pages, ISBN 0-02-913863-9
[4] Martin, Andre J., DRP: Distribution Resource Planning, The Gateway to True Quick
Response and Continuous Replenishment, John Wiley & Sons, Inc. New York, etc.,
revised ed., 1995, 329 pages, ISBN 0-471-13222-5
[5] Oracle Corporation, Oracle Inventory Reference Manual, Volume 3, Part No. A12991-2,
March 1994
[6] Vollman, Thomas E., Berry, William L., Whybark, D. Clay, Manufacturing Planning and
Control Systems, 3rd ed., Richard D. Irwin Inc., Homewood, Boston, 1992, ISBN 0-256-
08808-X
page 8 of 9
9. [7] Silver, Edward Allen, Pyke, David F., Peterson, Rein, Inventory Management and
Production Planning and Scheduling, 3rd ed., John Wiley & Sons, Inc., New York, etc.,
1998, 754 pages, ISBN 0-471-11947-4
[8] Smith, Bernard T., Focus Forecasting: Computer Techniques for Inventory Control, CBI
Publishing Company, Inc., Boston 1978, 258 pages, ISBN 0-8436-0761-0
[9 Smith, Bernard T., Focus Forecasting and DRP: Logistics Tools for the Twenty-first
Century, 1st ed., Vantage Press, New York, 1991, 227 pages, ISBN 0-9876-5432-1
[10] Thormählen, Volker, Inventory Valuation according to German Commercial and Tax
Legislation, Version 2.1, Cologne / Germany, March 20, 1996, 24 pages, 5 tables, 27
diagrams, 7 literature sources
[11] Tyworth, John E., Guo, Yuanming, Ganeshan, Ram, Inventory Control under Gamma
Demand and Random Lead Time, in: Journal of Business Logistics, Vol. 17 (1996), No.
1, p. 291 - 304 (Numerical methods to find optimum joint (s, Q) solutions)
11 Contact address
Dr. Volker Thormählen
Bull GmbH
Theodor-Heuss-Str. 60 - 66
51149 Köln-Porz
Germany
Tel.: + 49 (0) 2203 305-1719
Fax: + 49 (0) 2203 305-1699
Email: volker.thormaehlen@bull.de
volker.thormaehlen@doag.org
dr.volker@thormahlen.de
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