Purpose
The purpose of this document is to define the conversion approach to create Maintenance Planning Bucket in S/4 HANA.
A Maintenance Planning Bucket is a logical container or grouping tool used by maintenance planners to organize and manage maintenance orders and notifications for a specific time period and scope. The scope of a planning bucket includes time, but also other important attributes of the maintenance jobs.
Conversion Scope
The scope of this document covers the approach for converting active Revision from Legacy Source Systems into Maintenance Planning Bucket in S/4HANA.
In Syensqo, Maintenance Planning Buckets are primarily used to release maintenance orders, enabling material staging, permit processing, and job scheduling, while preventing further structural changes to the planning data.
There are currently two types of revisions in the source systems:
- Event-Based
- Weekly revisions.
The conversion scope will include only the migration of Event-Based revisions into Maintenance Planning Buckets. Weekly revisions will be handled as part of cutover activities and triggered via batch jobs.
However, from a conversion perspective, the mapping from legacy to target Maintenance Planning Buckets for Weekly revisions will still be maintained. This ensures that downstream objects—such as Notifications and Work Orders—can correctly map to the target Maintenance Planning Bucket.
The data from legacy system includes:
1. All valid legacy Revision based on Maintenance Plants in scope
The data from legacy system excludes:
1. Weekly Revisions
| Source | Scope | Source Approx No. of Records | Target System | Target Approx No. of Records |
|---|---|---|---|---|
| PF2, WP2 | Valid Revisions | 3,000 | S/4HANA | 3,000 |
| DCT | Revisions for plants which do not have data existing from PF2 and PF2 | nnn | S/4HANA | nnn |
Additional Information
Multi-language Requirement
Revision does not have multi language support. Revision text will be migrated using EN logon.
Document Management
Not Applicable
Legal Requirement
Not Applicable
Special Requirements
Specify any special requirements or considerations that may impact the data conversion process based on specific locations, regulatory compliance or system limitations. Clearly outline any regional or localization requirements such as country-specific data formats, legal reporting obligations or industry standards that must be adhered to (e.g., localization rules for countries like China).
If the data conversion involves third-party systems or external data sources, such as Icertis, describe any additional requirements related to data mapping, transformation logic, validation rules or security measures that must be followed.
Target Design
With Functional input, document the technical design of the target fields that are in the scope of this document.
The technical design of the target for this conversion approach.
| Table | Field | Data Element | Field Description | Data Type | Length | Requirement |
|---|---|---|---|---|---|---|
| EAM_PLNGBKT | MAINTPLANNINGBUCKETUUID | SYSUUID_X | UUID in X form (binary) | 16 | 0 | Mandatory |
| EAM_PLNGBKT | MAINTPLANNINGBUCKETTYPE | EAM_PLNGBKTTYPE | Maintenance Planning Bucket Type | 3 | 0 | |
| EAM_PLNGBKT | MAINTENANCEPLANNINGPLANT | IWERK | Maintenance Planning Plant | 4 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETLABEL | EAM_PLNGBKTLABEL | Label used for identifying the Maintenance Planning Bucket | 40 | 0 | |
| EAM_PLNGBKT | MAINTPLANNINGBUCKETDESCRIPTION | EAM_PLNGBKTDESC | Description of the Maintenance Planning Bucket | 40 | 0 | |
| EAM_PLNGBKT | NROFMAINTPLNGBUCKETSINADVANCE | EAM_NMBROFBUCKETSINADVANCE | Number of planning buckets the system will create in advance | 3 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETSTARTDATETIME | EAM_PLNGBKTSTARTDATETIME | Start of the Maintenance Planning Bucket | 15 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETENDDATETIME | EAM_PLNGBKTENDDATETIME | End of the Maintenance Planning Bucket | 15 | 0 | |
| EAM_PLNGBKT | LASTCHANGEDATETIME | EAM_LASTCHANGEDAT | Date and time the planning bucket was last changed | 15 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETGENERATIONDATE | EAM_GENERATIONBASEDATE | Date based on which the planning bucket was calculated | 8 | 0 | |
| EAM_PLNGBKT | REFMAINTPLANNINGBUCKET | SYSUUID_X | UUID in X form (binary) | 16 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETLABELPATTERN | EAM_PLNGBKTLABELPATTERN | Template used for the labels of generated planning buckets | 60 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETSORTFIELD | EAM_PLNGBKTSORTFIELD | Sort field | 16 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETRECURRENCETYPE | EAM_PLNGBKTRECURRENCETYPE | Specifies the recurrence of the planning bucket, e.g. weekly | 15 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETDURATION | EAM_PLNGBKTDURATION | Duration of the Maintenance Planning Bucket | 10 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETDURATIONUNIT | EAM_PLNGBKTDURATIONUNIT | Unit for Duration of Maintenance Planning Bucket | 3 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBCKTRCRRCINTERVAL | EAM_PLNGBKTRECUREVERY | Specifies the interval of recurrence, e.g. every 3 weeks | 5 | 0 | |
| EAM_PLNGBKT | PERSONRESPONSIBLE | EAM_PERSONRESP_CHAR8 | Person Responsible | 8 | 0 | |
| EAM_PLNGBKT | MAINTENANCEEVENT | REVNI | Revision for Plant Maintenance and Customer Service | 8 | 0 | |
| EAM_PLNGBKT | MAINTORDERFORADMINISTRATION | AUFNR | Order Number | 12 | 0 | |
| EAM_PLNGBKT | MAINTPLNGBUCKETSTATUSOBJECT | J_OBJNR | Object number | 22 | 0 | |
| EAM_PLNGBKT | MAINTENANCEPLANNINGBUCKET | EAM_PLNGBCKT_OBJNR | Object Number of Maintenance Planning Bucket | 20 | 0 | |
| EAM_PLNGBKT | SYSTEMSTATUSTEXT | J_STEXT | System status line | 40 | 0 | |
| EAM_PLNGBKT | MAINTENANCESYSTEMSTATUSCODE | J_STATUS | Object status | 5 | 0 | |
| EAM_PLNGBKT | MAINTENANCEPLANT | WERKS_D | Plant | 4 | 0 | |
| EAM_PLNGBKT | .INCLUDE | ASM_MPBKT_INCL_EEW_PS | Persistence Include for Maintenance Planning Bucket | 0 | 0 | |
| EAM_PLNGBKT | DUMMY_ASM_MPBKT_INCL_EEW_PS | CFD_DUMMY | Custom Fields: Dummy for Use in Extension Includes | 1 | 0 | |
| T352R | IWERK | IWERK | Maintenance Planning Plant | 4 | 0 | |
| T352R | REVNR | REVNI | Revision for Plant Maintenance and Customer Service | 8 | 0 | |
| T352R | REVBD | REVBD | Date of revision start | 8 | 0 | |
| T352R | REVBZ | REVBZ | Time of revision start | 6 | 0 | |
| T352R | REVED | REVED | Date of revision end | 8 | 0 | |
| T352R | REVEZ | REVEZ | Time of revision end | 6 | 0 | |
| T352R | REVTX | REVTX | Revision description | 40 | 0 | |
| T352R | REVAB | REVAB | Indicator: Revision completed | 1 | 0 | |
| T352R | PM_OBJTY | PM_OBJTY | Object Type of CIM Resources for Work Center | 2 | 0 | |
| T352R | GEWRK | GEWRK | Main work center for maintenance tasks | 8 | 0 | |
| T352R | EQUNR | EQUNR | Equipment Number | 18 | 0 | |
| T352R | TPLNR | TPLNR | Functional Location | 30 | 0 | |
| T352R | PSPEL | PS_PSP_ELE | Work breakdown structure element (WBS element) | 8 | 0 | |
| T352R | AUFNR | NW_AUFNR | Network number | 12 | 0 | |
| T352R | AENAM | AENAM | Name of Person Who Changed Object | 12 | 0 | |
| T352R | AEDAT | AEDAT | Changed On | 8 | 0 | |
| T352R | ERNAM | ERNAM | Name of Person who Created the Object | 12 | 0 | |
| T352R | ERDAT | ERDAT | Date on Which Record Was Created | 8 | 0 | |
| T352R | OBJNR | J_OBJNR | Object number | 22 | 0 | |
| T352R | REVTY | DIWPS_REVTY_CORE | Revision Type | 2 | 0 | |
| T352R | OBJID | LGWID | Object ID of the Work Center | 8 | 0 | |
| T352R | VAPLZ | GEWRK | Main work center for maintenance tasks | 8 | 0 | |
| T352R | VAWRK | WERGW | Plant associated with main work center | 4 | 0 | |
| T352R | EXTAPPL | DIWPS_EXT_APPL | External Application | 2 | 0 | |
| T352R | EXTREF | DIWPS_REV_EXT_REF | External Reference to Revision | 20 | 0 |
Data Cleansing
All data cleansing should take place in the data source system as defined in this document, unless system limitations prevent it.
If data cleansing is managed outside of the source system (e.g. Syniti Migrate, 3rd Party Vendor, DCT), the necessary documentation must be produced and appended to this deliverable for sign-off.
| ID | Criticality | Error Message/Report Description | Rule | Output | Source System |
|---|---|---|---|---|---|
| 9101-001 | C1 | Invalid, Inactive or no Inactive or no Cost Centres linked to Revision | Revision as per Relevancy Criteria assigned with a Cost Centre which does not belong below: 1. Cost Centre (FI) as per Relevancy Criteria | All key fields | PF2, WP2 |
| 9101-002 | C1 | Invalid, Inactive or no WBS linked to Revision | Revision as per Relevancy Criteria assigned with a WBS which does not belong below: 1. Work Breakdown Structure (PS) as per Relevancy Criteria | All key fields | PF2, WP2 |
| 9101-003 | C1 | Invalid, Inactive or no Inactive or no Work Centres linked to Revision | Revision as per Relevancy Criteria assigned with a Work Centre which does not belong below: 1. Work Centre as per Relevancy Criteria | All key fields | PF2, WP2 |
Conversion Process
The high-level process is represented by the diagrams below.
The following represents the high-level process for Source System Extraction:
The following represents the high-level process for DCT:
Data Privacy and Sensitivity
Summarize Data Privacy and Sensitivity Requirements, if anyExtraction
Extract data from a source into Syniti Migrate. There are 2 possibilities:
- The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. There are 3 methods:
- Perform full data extraction from relevant tables in the source system(s).
- Perform extraction through the application layer.
- Only if Syniti Migrate; cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
- The data does not exist (or cannot be converted from its current state). The data is manually collected by the business directly in Syniti Migrate. This is to be conducted using DCT (Data Collection Template) in Syniti Migrate
The agreed Relevancy criteria is applied to the extracted records to identify the records that are applicable for the Target loads
Extraction Run Sheet
| Req # | Requirement Description | Team Responsible |
|---|---|---|
| 1 | Extract data from source system based on relevancy rule | Data Team |
| 2 | Google Sheet report pre-populated with PF2 and WP2 information to be generated based on relevancy criteria. | Data Team |
Selection Screen
If applicable, this section will give the details on any selection screen parameters, including the parameter type, that are required to be entered to ensure consistent data extracts.| Selection Ref Screen | Parameter Name | Selection Type | Requirement | Value to be entered/set |
|---|---|---|---|---|
Data Collection Template (DCT)
Target Ready Data Collection Template will be created for Data Object data with exception of some fields which require transformation as mentioned in the transformation rule.<Object> DCT Rules
| Field Name | Field Description | Rule |
|---|---|---|
Extraction Dependencies
List the steps that need to occur before extraction can commence
| Item # | Step Description | Team Responsible |
|---|---|---|
| 1 | Only Revision linked to relevant Plants should be extracted. | |
Transformation
The Target fields are mapped to the applicable Legacy field that will be its source, this is a 3-way activity involving the Business, Functional team and Data team. This identifies the transformation activity required to allow Syniti Migrate to make the data Target ready:
- Perform value mapping and data transformation rules.
- Legacy values are mapped to the to-be values (this could include a default value)
- Values are transformed according to the rules defined in Syniti Migrate
- Prepare target-ready data in the structure and format that is required for loading via prescribed Load Tool. This step also produces the load data ready for business to perform Pre-load Data Validation
Transformation Run Sheet
| Item # | Step Description | Team Responsible |
|---|---|---|
1 | Ensure all mapping tables are up to date. | Syniti |
2 | In dspMigrate, select the wave –R3 S4/HANA – Plant Maintenance | Syniti |
3 | Go to Process Area Launch and Process the Object – Maintenance Planning Bucket | Syniti |
4 | Review and Validate Error and Preload Reports | Syniti |
5 | Execute the transformation to prepare the target tables | Syniti |
6 | Validate data from pre-load and invalid reports by region | Business/Data owner |
7 | Generate export(load) file (If load tool is not dspIntergrate) | Data Team |
Transformation Rules
| Rule # | Source system | Source Table | Source Field | Source Description | Target System | Target Table | Target Field | Target Description | Transformation Logic |
|---|---|---|---|---|---|---|---|---|---|
Transformation Mapping
Use the exact name and reference this section in the “Transformation rules” above| Mapping Table Name | Mapping Table Description |
|---|---|
Transformation Dependencies
List the steps that need to occur before transformation can commence| Item # | Step Description | Team Responsible |
|---|---|---|
Pre-Load Validation
Project Team
The following pre-load validations will be performed by the Project Team.Completeness
| Task | Action |
|---|---|
Verify Record Count | Data team to verify that the total number of relevant records from the source systems is equal to the total number of records in the Preload and Load Sheets. |
Accuracy
| Task | Action |
|---|---|
Conversion Accuracy | Data team to verify that all fields below meet pass the checks: 1. Mandatory Fields 2. Field and Value Mapping Correctness 3. Null Checks 4. Text Length Checks |
Review error reports | Review and correct the errors. Achieve a zero-error record count as much as possible. Raise defects for data remediated and requiring a correction in the source data. |
Business
The following pre-load validations will be performed by the business.Completeness
| Task | Action |
|---|---|
Verify Record Count | Business team to verify that the total number of relevant records from the source systems is equal to the total number of records in the Preload and Load Sheets. |
Accuracy
| Task | Action |
|---|---|
Conversion Accuracy | Business to verify that all the data in the load table/file is accurate as per endorsed transformation/mapping rules (and signed-off data) |
Load
The load process includes:
- Execute the automated data load into target system using load tool or product the load file if the load must be done manually
- Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation
Load Run Sheet
| Item # | Step Description | Team Responsible |
|---|---|---|
Load Phase and Dependencies
Identify the phase as to “when” the load for this object will occur. <Pre-Cutover, Cutover, Post Cutover> and list the steps that need to occur before the load can commence
Configuration
List the Configurations required before loading can commence
| Item # | Configuration Item |
|---|---|
| 1 | Plant |
| 2 | Planning Bucket Type |
Conversion Objects
| Object # | Preceding Object Conversion Approach |
|---|---|
| N/A | |
Error Handling
The table below depicts some possible system errors for this data object during data load. All data load error is to be logged as defect and managed within the Defect Management
| Error Type | Error Description | Action Taken |
|---|---|---|
Post-Load Validation
Project Team
The following post-load validations will be performed by the Project Team.Completeness
| Task | Action |
|---|---|
Verify Count | Data team to verify the record count created in target S/4 HANA by accessing post load reports in dspMigrate or standard reports from S/4 HANA. |
Verify Logs | Check if there is data that failed to load and perform the necessary actions (e.g. register as post load issue, or attempt to load the record again, etc.). |
Accuracy
| Task | Action |
|---|---|
Conversion Accuracy | Data team to verify that the Measuring Point data in target S/4 HANA were loaded correctly via dspMigrate post load reports or standard reports from S/4 HANA. |
Business
The following post-load validations will be performed by the business.Completeness
| Task | Action |
|---|---|
Verify Count | Download Post Load Reports from dspMigrate and verify that the record count loaded in the target S/4 HANA is the same count as of the endorsed load file. |
Accuracy
| Task | Action |
|---|---|
Conversion Accuracy | Verify that the Measuring Point data in target S/4 HANA were loaded correctly via dspMigrate post load reports or standard reports from S/4 HANA. |
Key Assumptions
- Maintenance Planning Bucket is in scope based on data design and any exception requested by business.
- Data cleansing has met the required percentage threshold for the specified mock cycle and all preparation activities have been completed.
Any additional key assumptions.
See also
Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.