MSc. PhD.

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Profile

SAP CONSULTANT

Materials Management (MM) implementations and knowledge of Sales and Distribution (SD) and ABAP programming obtained from positions in several industries. Professional, flexible, creative, and service-oriented. Offering a unique combination of teamwork and analytical skills with the ability to assess international projects and create cost-effective solutions for global clients.

RESEARCH AND DEVELOPMENT

Evolutionary Computing (GP and GA) applied to Design Optimization. How optimization technologies based on computer programmes can support an engineer in searching for the best possible design.

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Latest News

29.02.2016

Central Maine Power - Augusta (ME, USA)

Smart Care logistics workshop.

03.10.2015

Abeinsa - New Delhi (India)

SAP logistics training ang project Go-Live.

16.02.2015

Abeinsa - Mexico City (Mexico)

SAP Material Management training.

18.05.2014

Abeinsa Power Struct. - Vadodara (India)

SAP support manager.

11.11.2013

Befesa - Madrid (Spain)

SAP SLO: company splitting process.

SAP Overview

SAP is the leading ERP software in the world designed to optimize business processes at a lower cost than traditional solutions. It can support procurement, sales, finance and other essential corporate functions integrated into one solution set.

SAP is no ordinary software package it inspires devotion and passion, but at the same time frustration if not implemented properly.
An SAP Consultant is a professional with business and communication skills helping clients implement cost-effective solutions based on best practices.

SAP Consultancy

My experience in international SAP consultancy projects can deliver the following expertise:

  • Integration: understand the seamless flow of data in SAP connecting finance, purchasing and sales.
  • Documentation: Business Blueprint, test cases, end user manuals.
  • Functional specification: gap analysis, ABAP developments.
  • Configuration: map each step of the business process into SAP.
  • Training: help clients get a better insight into SAP.

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Evolutionary computing

Evolutionary Computing studies how computer programmes can simulate processes found in nature to assist in optimization tasks. The main principles are:

  • Maintain a population of solutions.
  • Measure the fitness of individuals at competing with each other.
  • Evolve according to Darwin's natural selection rules to increase quality.
  • Explore diversity with sexual operators such as crossover or mutation.
  • Breed the population over generations.

My research deals with Genetic Programming and Genetic Algorithms.

Design optimization

Design optimization technologies support an engineer in searching for the best possible design.

The size and complexity of a design task involves a large numbers of variables. Engineers are faced with the challenge to search for the best overall design by considering trade-offs between certain attributes like cost or weight and performance.

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Photo album

SAP team in Houston, TX (USA) Factory workers at SAP project in Vadodara, Gujarat (India) SAP key users and factory manager in Vadodara, Gujarat (India) Research presentation at ASMO Conference in Harrogate (UK) ASMO Conference attendees in Harrogate (UK) PhD graduation in Bradford, West Yorkshire (UK) Welcome party at Postdoctoral seminar in Hiroshima University (Japan) SAP projects abroad enable sightseeing, here Taj Mahal (India) Video testimonial to call for volunteers in a local Alzheimer Association

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PROFILE

Contents

1. Professional Experience

SAP consultant specializing in Materials Management and ABAP programming, with knowledge of Sales and Distribution and Business Intelligence.

2016-present UST GLOBAL (Madrid - Spain)

    IBERDROLA (Bilbao)
  • SAP Corporate integration of logistics processes and interfaces for group company Central Maine Power (ME, USA) following IS-U implementation.

2008-2016 COMMON MANAGEMENT SOLUTIONS (Madrid - Spain)

    ABENGOA
  • Implementation of MM module as part of the new concessions model for 2 group companies. Several meetings, training and go-live held in New Delhi (5 weeks) and Mexico City (2 weeks). Tasks included MM customizing for Purchase Requisition, Purchase Order, stock management and invoice verification. Additionally, customizing for SD invoicing and Projects.
  • On-site support project (3 months) for Abeinsa Power Structures factory in Vadodara (India). Tasks included MM, PP, PM, SD, FI issues solution with support of functional consultants, progress reports and identification of risks, the latter motivating the replacement of a key user following poor aptitude despite many training sessions.
  • MM remote roll-outs for several group companies in South America and Middle East involving standard purchasing procedures from requisition to invoice, workflow management and smartform design.
  • MM consultant in SLO project to split waste management company Befesa from parent company Abengoa. Main tasks included review of organizational units and master data, analyses of data to be deleted, integration tests, team liaison with SAP SLO consultant. The project team achieved a very low rate of issues after go-live.
  • 4 months MM implementation for Energoproject in Gliwice (Poland): guidance on best practices, customizing, writing of documentation for the designed business scenarios and training.
  • Coordination of a multicultural team of 8 consultants in Houston (TX, USA) leading the change management of the MM department according to SAP standards for IT company Telvent (9 months). Full responsibility for data migration into SAP via LSMW.
  • INSTITUT GUTTMANN / OBRA HOSPITALARIA SAN JUAN DE DIOS
  • MM Implementation for hospitals and maintenance of the solution after go-live.
  • Support required ABAP development.
  • OXFORD UNIVERSITY PRESS
  • Management of a one year project to launch an E-learning website in Spain. Responsibilities included the coordination of the development teams in UK and Spain, preparation and execution of user scenarios for process validation.
  • FERROVIAL
  • BI project involving the review of the data model and reports after the merge of several companies

2004-07 SELF-EMPLOYED (León - Spain)

  • Part-time IT consultant and web site design.

2001-03 UNIVERSITY OF BRADFORD (Bradford - UK)

  • Research project funded by the European Commission with partners from the Technical University of Denmark (Coordinator), Austria, Germany and Sweden.
  • Optimization of a heat and power plant based on a Stirling engine for biomass fuels.
  • The optimization increased the plant efficiency by 10%.

2002 JAGUAR RACING (Milton Keynes - UK)

  • Consultancy project in partnership with Altair Engineering UK.
  • Weight optimization of the front wing for the R3 Formula One car.
  • Development of an optimization methodology based on a genetic algorithm and Altair OptiStruct FEM software that achieved 15% saving over the baseline weight of the wing.
  • A variation of final results was implemented onto the latest R3 model.

1997-2000 UNIVERSITY OF BRADFORD (Bradford - UK)

  • Research project supported by the Training and Mobility of Researchers (TMR) programme of the European Commission.
  • Development of a C++ computer code for approximation model building in design optimization based on the response surface methodology and genetic programming.
  • Testing on applications with numerically simulated and experimental responses.

1992-93 COUDERIOUX (Design and manufacturing of steel structures - Blois - France)

  • Consultancy project supported by the European programme COMETT.
  • Full responsibility for the computerization of the design office:
  • Choice of a CAD software/hardware solution based on bocad-3D.
  • Training of technical staff in all aspects of the job with in-house user manuals.
  • The company achieved a 30% reduction in production time and an improvement in the overall quality.

1992 PRECESA (Precast concrete products manufacturer - León - Spain)

  • Payroll computer programme to control beam production and working hours.
  • This automation made possible the assignment of one person to other functions.

2. Education

2008 INTECO (León - Spain)

  • Java technology advanced programming course (220 hours).

2007-08 INTECO (León - Spain)

  • Master Degree in SAP Business Programming Web AS Focus Java and ABAP.
  • SAP Certification: NetWeaver Development Consultant Focus ABAP.

1997-2000 UNIVERSITY OF BRADFORD (Bradford - UK)

  • PhD
  • Thesis: Design optimization based on genetic programming.
  • Publication of more than 20 papers at different conferences about engineering optimization and evolutionary computing.

1994-95 UNIVERSITY OF BRADFORD (Bradford - UK)

  • MSc in Structural Engineering (Distinction).
  • Dissertation: development of a GUI in Visual C++ for the graphical representation of the optimization history in MARS design optimization software.

1987-92 UNIVERSITY OF LEÓN (León - Spain)

  • BSc (Hons) Industrial Engineering (2.1). Specialization in structural engineering.
  • Final year project: development of a programme in C language to analyse 2-D and 3-D rigid jointed frames (1 year).

1985-87 COLEGIO MARISTA SAN JOSÉ (León - Spain)

  • Secondary School - 'A' level equivalents in Mathematics, Chemistry and Physics.

1981-85 ATHÉNÉE CHARLES JANSSENS (Brussels - Belgium)

  • Secondary School.

3. Languages

  • Spanish, French: mother tongues.
  • English: fluent.

4. Other Information

2004-present Community service (León - Spain)

  • Volunteering in the local branch of an Alzheimer Association
  • Creation of a quarterly newsletter.
  • Fundraising and awareness events (fairs, world Alzheimer's day, flea market, etc.).
  • Testimonial in a promotional video to call for volunteers.

2007 Volunteer training course (León - Spain)

2001 Hiroshima University (Japan)

  • Royal Society Postdoctoral visit to the Department of Mechanical System Engineering.

1999 First ASMO UK / ISSMO conference on Engineering Design Optimization (Ilkley, UK)

  • Member of the Organizing Committee.

1988-90 Member of the Student Union - University of León.

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Design Optimization with Genetic Algorithms

Contents

1. Design Optimization

After the numerical analysis (e.g. finite element method) of the behaviour of an engineering system, an important goal of the designer is to improve and to optimize its performance. The task of design optimization is to support an engineer in searching for the best possible design. The "optimal" design is a system that highly corresponds to the designer's desired concepts and at the same time satisfies all the functional and manufacturing requirements.

The importance of design optimization was first recognised by the aerospace industry where aircraft structural designs are controlled by weight. In other industries like civil or mechanical engineering, cost may be the primary considerations. Figure 1 shows a typical design process with an optimization technology applied to the front wing of a Formula One car (inspired in my consultancy project with Jaguar Racing, see case studies below).

CONCEPT   FEM MODEL   OPTIMIZATION   FINAL DESIGN
F1 car drawing Front wing model Optimization problem F1 car
F1 car drawing   Front wing model   Minimize mass subject
to max. deflection
  F1 car
Figure 1. Front wing optimization process

The problem can be stated as to find the set of parameters that minimize an objective function subject to a set of behavioural constraints. The group of parameters that can be varied to improve the design are called design variables (DV) and can describe cross-sectional dimensions, material properties, shape of a structure, etc. They are denoted by the vector:

x = ( x1, ..., xN )      where N: number of DV

The optimization process implies that there is an objective function F0(x) that can be improved and that provides a basis for choice between alternative acceptable designs. It can reflect the cost of a system or some simplified criteria such as weight.

The constraint functions impose limitations on the behavioural characteristics, and can be various response quantities such as stresses, aerodynamic drag, etc..

The optimization problem is defined as:

MinimizeF0(x)
subject to constraints Fj(x 1  ( j=1,...,M ),   Ai  xi  Bi  (i = 1, ..., N)

where M:number of constraints, N:number of DV, A:lower bound, B:upper bound.

2. The problem: Computational cost and Noise

The application of design optimization to real-world problems suffers, in practice, from two difficulties:

  • High computational cost of the response analysis, e.g. FEM model.
  • Presence of noise in the response data.

The first problem has been mitigated by introducing approximation concepts to replace the objective function and/or the constraints of the problem with less expensive models. Response Surface Methodology (RSM) is a technique that traditionally uses polynomial models (to be used as approximations) created by performing a least-squares fit into a set of data, thus reducing the negative effect of numerical noise in the response function values (Figure 2a). The response can be represented graphically as a 3D surface or as contour plots (Figure 2b).

NOISY FUNCTION   APPROXIMATION FUNCTION    
Noisy function Approximation function   Contour plot
2a. Approximation of a 2D noisy function   2b. X-Y projection of a
3D contour plot
Figure 2. Approximations

One of the major problems in the application of approximation techniques is the necessity to select the structure of the approximation function. The most typically used linear (e.g. polynomial) are simple and easy to use, but the quality of approximations can be low, so the overall convergence of the technique can be slow.

The search through all possible combinations of individual regression components in the empirical model building would result in prohibitive computational effort. To search the design space in an adaptive and intelligent way, I have carried out research on the application of Genetic Programming for the creation of an approximation function structure of the best possible quality.

3. The Solution: Genetic Programming

An evolutionary algorithm (EA) is a computer-based system that evolves a solution to a problem by simulating processes found in nature, e.g. the Darwinian concept of survival of the fittest. One relatively new EA is genetic programming (GP). The GP paradigm deals with the problem of representation in genetic algorithms (GA) by increasing the complexity of the structures undergoing adaptation. Figure 3a shows the GP representation of an expression as a tree and Figure 3b shows how crossover creates 2 offsprings that become new candidate solutions to the problem.

GP tree representation    Crossover
3a. GP tree representation for:
a0+(a1*x1/x2+a2*x3)^2
  3b. Crossover
Figure 3. Genetic programming

The use of genetic programming for symbolic regression was first proposed by Koza. The advantage of symbolic regression over standard regression methods is that the search process works simultaneously on both the model specification problem and the problem of fitting coefficients, as opposed to conventional linear or nonlinear regression which involve finding the coefficients of a prespecified function.

The flexibility of genetic programming comes from its hierarchical structure and the fact that we do not specify the size, the shape and the structural complexity of the solution in advance, but these characteristics evolve as part of the solution to the problem.

For details about the methodology and applications, please refer to my PhD thesis.

4. Case Studies

Two applications are presented. Firstly, a discrete optimization combining genetic algorithm and FEM is carried out to reduce mass on a F1 car front wing. Secondly, genetic programming is applied to the approximation of a nonlinear data set in order to create an empirical model for the shear strength of RC deep beams.

4.1. Genetic Algorithm: Weight Optimization of a F1 Car Front Wing

R3 F1 car
Figure 4. R3 F1 car

R3 front wing
Figure 5. Front wing

4.1.1. The problem

The design of Formula One cars (Figure 4) takes approximately 4 months and has to go through as many iterations as possible in an effort to optimize every aspect of the car. In such a competitive environment, Jaguar Racing wanted to reduce weight in the R3 composite front wing . A robust technology was needed to optimize an already highly optimized design.

4.1.2. The methodology

A specific genetic algorithm was developed running on Altair FEM software OptiStruct in order to solve concurrently the carbon fibre orientations and the number of plies of the wing composite lay-up (Figure 5). The optimization problem was stated as to minimize the mass subject to FIA standards and aerodynamic loading.

4.1.3. The results
  • Initial results showed trends of the wing lay-up (e.g. biased more to bending in the middle of the wing and plies biased more to twist at the outer edge)
  • Final results showed up a new and innovative direction for the wing lay-up and a variation was put onto the latest model of the R3 car.
  • GA achieved 5% reduction over the baseline weight of the wing. Looking at only designable areas (Figure 5), GA achieved 15% weight reduction.
4.1.4. Read more

Download a technical paper (pdf, 596 KB) presented at Altair Engineering UK Conference and the press release (pdf, 262 KB) from the University of Bradford.

4.2. Genetic Programming: Shear Strength of RC Deep Beams

RC deep beam
Figure 6. RC deep beam

Experimental/predicted shear strength
Figure 7. Experimental/predicted shear strength

4.2.1. The problem

Reinforced Concrete (RC) deep beams are common structural elements characterised as being relatively short and deep, with a small thickness relative to the span or depth (Figure 6). Despite the large amount of research carried out over the last century, there is no agreed rational procedure to predict their shear strength failure mechanism. In addition, codes of practice (BSI, ACI) show poor agreement about their design.

4.2.2. The methodology

A genetic programming algorithm was applied to build an empirical model that predicts the shear strength of RC deep beams under 2 point loads. The model is evolved from a set of experimental data available in the literature and validated through a parametric study.

4.2.3. The results
  • Good agreement between the GP model and experiments (Figure 7).
  • Screening: GP identified irrelevant variables.
  • The behaviour described by the GP model was experimentally and computationally observed by other researchers.
  • As more experimental data and engineering knowledge become available, the GP prediction can be improved.
4.2.4. Read more

Download a paper (pdf, 165 KB) published in "Computers & Structures" Journal.

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SAP MM Business Blueprint

Contents

1. Introduction

The Business Blueprint (BBP) is one of the most important documents in the project management process of SAP Consultancy. The purpose of this document is to better understand how a company intends to run its business within the SAP System based on the outcome of requirement workshops. The key elements of the document are:

  • Organizational Structure
  • Master data
  • Business processes

The following sections give an overview of a business blueprint focused on the materials management (MM) area.

2. Materials Management

The Materials Management (MM) module in SAP covers all the activities and logistics tasks related to the procurement and control of the supply chain and supports its different phases: purchasing, goods receiving, inventory management, and invoice verification.

Purchasing integrates with other modules in the SAP system to ensure a constant flow of information:

  • Controlling (CO): purchase orders for materials intended for direct consumption and for services can directly be assigned to a cost center.
  • Financial Accounting (FI): purchasing maintains data on the vendors that are defined in the system jointly with Financial Accounting. The vendor master record represents the creditor account in financial accounting. Through purchase order account assignment, purchasing can also specify which G/L accounts are to be charged in the financial accounting system.

3. Organizational Structure

This section describes the organization of a company in the SAP system and how purchasing is integrated into this structure.

3.1. Purchasing Organization

The purchasing organization level is responsible for procuring materials or services for one or more plants and for negotiating general conditions of purchase with vendors. The purchasing organization assumes legal responsibility for all external purchase transactions.

3.2. Purchasing Group

The purchasing organization is further subdivided into purchasing groups which are responsible for day-to-day buying activities. A purchasing group can procure for several purchasing organizations and can be a user or department.

3.3. Company Code

The company code level represents an independent accounting unit with its own balance sheet and its own profit and loss statement.

3.4. Plant

The plant level is a logistics operational unit within a company code. It can be a branch office or a production facility. A plant can receive, store and issue materials.

3.5. Storage Location

The storage location is an organizational unit allowing the differentiation of material stocks within a plant. The physical location can be a room or some space identified on the floor.

4. Master Data

Master data in purchasing are key data stored in the system database for long-term procurement. The main data records are vendors and materials.

4.1. Vendor Master Data

The vendor master database contains information about the vendors that supply a company. This information is stored in individual vendor master records kept in a central repository for the whole company.

Since to the accounts department vendors are generally creditors (accounts payable), the vendor master record also contains accounting information, such as the relevant control account (reconciliation account) in the general ledger. Therefore, the vendor master record is maintained by both Accounting and Purchasing.

4.1.1. Vendor account group

Each vendor must be assigned to an account group which determines:

  • Type of number assignment (internal or external) and the range assigned to the vendor.
  • A search criteria for reports.
  • Which fields are displayed on the vendor master record screens and whether entries in these fields are mandatory or optional.
4.1.2. Vendor organizational levels and field description

The Vendor master data are structured as general, company code and purchasing data.

General
Data
Data that applies equally to each company code within the company (address, telephone number, etc.).
Company Data Company code level data (reconciliation account, etc.). Usually entered by the Finance department.
Purchasing Data Important purchasing data kept at purchasing organization level (contact person, order currency, etc.).

The table below shows a sample list of fields defining a vendor, column "L" is the maximum length of the corresponding coding in the system.

FieldLDescription
Organizational Information
Company code4Company code where the vendor is created.
Purchasing organization4Purchasing Organization where the vendor is created.
Account group4Classification defining common characteristics.
General Information
Name40Vendor name.
Street and house number60Address.
Postal Code10The format of the postal code is dependent on the country.
City40Vendor city.
Country2Vendor country.
Language2Language of communication with the vendor.
Control Information
Tax number16An identification number issued by the tax authorities to taxpayers. Each country has its own system. In countries where taxes are levied not just at national (or federal) level, but also at local level (by states or municipalities), multiple tax numbers may be issued. i.e. tax jurisdiction code for USA .
Payment Information
Bank country2Identifies the country in which the bank is located.
Bank key15Bank key under which bank data from the respective country is stored.
Bank account18Number under which the account is managed at the bank.
Control key2Key for checking the combination of bank number and bank account number and is country specific.
Accounting Information
Reconciliation Account10The reconciliation account in G/L accounting.
Cash management group10In cash management, vendors are allocated to planning groups by means of an entry made in the master record.
Payment terms4Key for defining payment terms composed of payment periods.
Payment method10List of payment methods which may be used in automatic payment transactions with this vendor.
Purchasing Information
Order currency3Key for the currency on which an order placed with a vendor is based.
Sales person30Responsible Salesperson at Vendor's Office.
Account with vendor12Account number which the vendor uses for our company.

4.2. Material Master Data

The material master database contains descriptions of all materials that a company procures. It is the central repository of information on materials for the whole company.

The integration of all material data in a single database eliminates the problem of data redundancy and permits the data to be used not only by purchasing, but by other applications such as Invoice Verification.

Material master records may be created and changed either centrally or by individual departments. In the latter case, the department will be responsible for continually updating the corresponding purchasing data.

4.2.1. Material types

Each material must be assigned to a material type which determines:

  • Type of number assignment (internal or external) and the range assigned to the material.
  • A search criteria for reports.
  • Which fields are displayed on the material master record screens and whether entries in these fields are mandatory or optional.
  • Account determination when the material is consumed.
  • Whether the material is intended for stock, and whether the material will be updated in terms of quantity and value.
4.2.2. Units of measure

The system distinguishes between different units of measure.

Unit of MeasureDescriptionExample
BaseUnit of measure in which the stocks of a material are managed. The system converts all quantities entered in other units to the base unit of measure.EA (each)
AlternativeIndividual departments (i.e. purchasing) may have their own units of measure.BOX, CARTON
Order unitAllows a material to be ordered in a unit differing from the base unit of measure. The order unit is proposed automatically in purchasing functions.1 BOX = 4 EA
1 PAL = 72 EA
4.2.3. Material organizational levels and field description

The material master data are structured as views. At plant level, the main views are basic data, purchasing and accounting.

Basic Data View Data applicable to all individual group companies and all plants (description, units of measure, etc.).
Purchasing View Data provided by the Purchasing department for a material (order unit of measure, tax indicator, etc.).
Accounting View This level contains accounting information related to valuation and price calculation (valuation class, price control, etc.).

The table below shows a sample list of fields defining a material, column "L" is the maximum length of the corresponding coding in the system.

FieldLDescription
Organizational Information
Industry sector1The industry sector determines which screens appear and in what order and which industry-specific fields appear on the individual screens.
Material type4The material type defines certain attributes of the material and has important control functions.
Plant4The plant level is a logistics operational unit within a company code.
Basic Data View
Material description40Text that describes the material. The description can be defined in any language supported by the system.
Base Unit of Measure3Unit of measure in which the material is managed. Quantities in other units of measure (alternative units of measure) are converted to the base unit of measure.
Material group9Key to group together several materials or services with the same attributes. Useful to Restrict the scope of analyses and search specifically for material master records via search helps.
Purchasing View
Base Unit of Measure3Unit of measure in which the materials are managed.
Order unit3Unit of measure in which the material is ordered.
Tax indicator1The tax indicator is used in the automatic determination of the tax code in Purchasing.
Accounting View
Valuation class4Determines the G/L accounts updated for a valuation-relevant transaction (such as a goods movement).

5. Business Processes

5.1. Business Scenario

A standard procurement cycle in SAP includes the following activities.

  1. Determination of requirements: a user can manually pass a requirement for materials to the purchasing department via a purchase requisition.
  2. Determination of the source of supply: the system helps the buyer to create requests for quotation and then enter the quotations or check existing purchase orders and conditions in the system.
  3. Vendor selection: the system simplifies the selection of vendors by making price comparisons between the various quotations.
  4. Purchase order processing: the system facilitates data entry by providing entry aids when entering purchase orders.
  5. Purchase order monitoring: the buyer can monitor the processing status of the purchase order at any time and can determine whether goods or an invoice have been received for the relevant purchase order item.
  6. Goods receipt: the system compares the goods receipt quantity with the purchase order quantity.
  7. Invoice verification: vendor invoices are checked for accuracy of prices and contents.
  8. Payment processing: financial accounting deals with vendor payments.

5.2. Purchase Requisition

When a need arises for a new purchase, the buyer enters a purchase requisition that determines what and how much to order and the delivery date. The Purchase Requisition is therefore an internal document with no header information (such as vendor details).

5.3. Purchase Order

A purchase order is a formal request or instruction from a purchasing organization to a vendor to supply a certain quantity of goods or services at or by a certain point in time.

A purchase order consists of a document header and a number of items. The information shown in the header relates to the entire order, for example, currency, date, terms of payment.

5.3.1. Purchase Order types

The purchase order type determines:

  • Number range assigned to the document.
  • Search criteria in reports.
  • A key parameter in the release strategy.
5.3.2. Price conditions

Price conditions can be setup in the purchase order in order to accommodate any agreement with the vendor. These conditions types are used in the calculation schema as the framework for price determination:

  • Gross price: base price.
  • Net price: gross price with any applicable discounts and surcharges.
  • Effective price: net price with allowance for taxes and delivery costs.
5.3.3. Release strategy

The release strategy defines the approval process for purchasing documents. The strategy specifies the release codes (users) and the sequence in which releases have to be effected. The assignment of the release strategy to a purchasing document is based on release conditions (price).

The release strategy can be linked to an SAP Business Workflow in order to automatically notify the user of any awaiting release process (SAP inbox, E-mail, etc.).

The following table shows an example of a release strategy applied to the total amount of a purchase order (P1, P2 and P3 are users in the system and Level 1 and Level 2 are levels for approval in order of precedence ):

PO TypePurch. Org.Company codePlantPurch. GroupAmount (€)Level 1Level 2
TTTTXXXXYYYYZZZZGGG0 - 4999P1
TTTTXXXXYYYYZZZZGGG≥ 5000P1P2
UUUUXXXXYYYYZZZZHHH≥ 0P3
5.3.4. Purchase Order form

A smartform is an SAP tool to define the format and content of purchasing document forms. The form determines the layout, what information needs to be printed and whether the output is sent to a printer or by E-mail.

5.4. Goods Receipt

Goods receipt is the process of receiving materials from a vendor with reference to a purchase order. The purchasing department can procure materials either for stock or for direct consumption.

Procurement for stock involves materials that are placed in storage following a goods receipt. The stock is therefore increased or reduced by the quantity received or issued. Automatic postings to stock and consumption accounts follow each goods movement. The value and the quantity of the stocked material are updated in the material master record.

On the other hand, procurement for direct consumption requires an account assignment, for example a cost center. On goods receipt, the material or service counts as having been consumed and the consumption accounts in Financial Accounting are posted. The total quantity and value of existing stocks of the material are not affected.

5.4.1. The document concept

A document must be generated and stored in the system for every transaction that causes a change in stock. When posting a goods movement in the SAP System, the following documents are created:

  • Material document: a material document is a proof of physical goods movements and serves as a basis of information for subsequent processes. It contains a header (date, etc.) and one or more items describing a movement type.
  • Accounting document: If the movement is relevant for financial accounting, an accounting document is created. The G/L accounts involved in a goods movement are updated through automatic account assignment.
5.4.2. The movement type concept

A movement type differentiates between the various goods movements. It plays a central role in updating the quantity fields, in the automatic account determination and also determines the structure of the screen .

The following table shows the basic movement types:

Movement TypeDescription
101 (+) Goods receipt for purchase order.
102 (-) Cancellation of movement type 101 (due to error, etc.).
122 (+) Return delivery to supplier (due to bad quality, etc.).
123 (-) Reversal of return delivery, i.e. cancellation of movement type 122.

5.5. Logistics Invoice Verification

In Materials Management, the procurement process is concluded by the invoice verification process where contents and prices of incoming invoices from a vendor are checked for accuracy.

The invoice generally makes reference to a business transaction, i.e. purchase order. In such case the system retrieves data stored in the database (master and transaction data) in order to compare suggested quantities and values for each item from the purchase order with the data from the vendor invoice.

During the invoice verification process, the balance specifies whether the vendor invoice amount is equal to the total amount of invoice items, taxes, and unplanned delivery costs. If the balance is zero then the invoice is posted and logistics and accounting documents are created. The appropriate information is passed on to the finance department for payment and analyses.

5.5.1. Invoice Master Data
  • Material master data: information on the materials bought by or produced in the company.
  • Vendor master data: information on the suppliers that a company deals with.
  • Accounting master data: information on G/L accounts.
5.5.2. Invoice Transaction Data
  • Purchasing document: information on the purchase order such as amounts, quantities and tax information.
  • Material document: information on the goods receipt quantities.
  • Accounting document: information on individual postings if the good receipt is valuated.
5.5.3. Invoice Documents
  • Invoice logistics document: information on the invoice created with reference to a preceding document such as a purchase order.
  • Invoice accounting document: financial information of the invoice that triggered the posting. It consists of one or more line items representing individual postings to an account.
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Privacy Policy

Luis Alvarez informs you that in order to enquire through the contact form or by E-mail you have to provide certain personal data. In compliance with Spanish law "Ley Orgánica 15/1999 de Protección de Datos de Carácter Personal (LOPD)" your personal data have the only purpose of providing the requested information. The processing of the data is enforced under current Spanish regulations and applies to all nationals and foreigners using this website.

Luis Alvarez also informs you that the personal data you provide will be processed confidentially and used exclusively for the above purpose. Therefore, your data will not be disclosed to any third party.

In compliance with article 21 of Spanish law "Ley 34/2002 de Servicios de la Sociedad de la Información y Comercio electrónico (LSSI)", when you request information you specifically give your consent to send this information by E-mail at the address you provide. Should you, at any time, no longer consent to the collection and use of your personal information as outlined in this policy, please notify Luis Alvarez by E-mail at info@luis-alvarez.es.

This privacy policy may be amended from time to time without notice to you. After any such amendments, the use of this website signifies your acceptance thereof.

If you have any question regarding this privacy policy please send an e-mail to info@luis-alvarez.es.