Industrial Projects History

Click to expand the following past research projects of the Production & Logistics Networks Workgroup.

Problem: What is the optimal distribution network structure in terms of logistics cost and customer service levels?

What is the optimal number of distribution levels and number of sites per level?
What are the locations for distribution centers that offer the lowest transportation and warehousing costs?
What safety stock levels are required to maintain high customer satisfaction
Which products should be Made-To-Stock and which Make-To-Order?

Methodology
Distribution footprint analysis
Location-based analysis
ABC/XYZ Analysis
Safety Stock Calculation

Results

10% savings in logistics costs per year
Development of a distribution network with four distribution centres
Allocation of products to each DC
Safety Stock Levels calculated for each DC

Problem: How can a traditional logistics service provider satisfy the growing demand for 4PL activities?

Growing market demand due to increases in product variants and production complexity, advancements in IT, growing global competition.
Need to develop from traditional logistics service provider (e.g. focusing on transportation) to 4PL.
What competencies are needed? What kind of network is needed?

Methodology
Workshops with involved parties to identify service offering, required competencies, network partners
Market research
SWOT analysis

Results

Developed 4PL business model
Identified existing and required competences (e.g. IT, coordination)
Preparation of first 4PL offer
4PL companies offer coordination services of logistics activities and do not own logistics assets.

Problem: How can we improve supplier quality prediction through integrating distributed, large-scale data (Big Data)?

Which factors influence supplier quality?
Which data from distributed sources within the company is accessible and relevant?
Which prediction method should be used within an Early Warning System?

Methodology
Multiple Linear Regression Analyses
Panel Data Analysis
Framework for an Early Warning System

Results

Set up of a formalized prediction model with high model fit (83%)
Discovering correlations with new kinds of variables and confirming the use of existing variables
Providing an operational, qualitative framework for supplier quality prediction

Problem: No information about actual system loads and problems to define and meet due dates?

Replacing manual production planning and controlling by a data based IT solution.
Identification of bottleneck systems
Targeted future-oriented personnel planning

Methodology
Logistic capabilities analysis
Logistics-IT-system design
Coaching
Implementation management and final performance test

Results

Defined priority areas and concrete actions
Transparency of current situation by KPIs
Reduced work in process levels
Halved mean throughput times per order
Realistic scheduling
Improved in time delivery from 60% to 80%
Improved due date reliability from 20% to over 55%

Problem: How to cope with two parallel and distinct warehousing processes and procedures at two locations?

How can cost savings in warehousing be realized without threatening the efficiency of grid maintenance?
▪ How can the different requirements on grid maintenance in rural and metropolitan be aligned in on warehousing strategy?

Methodology
Business Process Documentation and Analysis
ABC Analysis
Safety Stock Calculation

Results

Identification of common items and their retrieval and reorder frequencies
Documentation of warehousing-related business processes and IT systems
Development of a post-merger warehousing strategy

Problem: As a result of high inventories, a company faced high net working capital while at the same time seeing low due-date reliability and long delivery times among their products.

Develop a supply chain strategy to overcome low due-date reliabilities and long delivery times
Define the main market requirements and align the strategy according to the market
Define the most relevant KPIs

Methodology
Structured expert interviews
Business process analysis (in production)
Statistical analysis of production KPIs (e.g., due date reliability)

Results

Identification of supply chain weaknesses
Derivation of different possible business strategies
Development of a concept for a dynamic supply chain strategy decision support model (how and where to insert decoupling points)

Problem:

The 9-month R&D-project “Determining Punctuality Potentials of the international steel company ThyssenKrupp Steel Europe” has been conducted in cooperation with the project-partner IFA (Leibniz Universität Hannover).
The logistical analysis implies two perspectives: order processing view and aggregate-oriented view.

Methodology
Logistics oriented statistical analysis
Cluster analysis

Results

The identified potentials for improving the delivery performance of the company have been structured in a ranking matrix according to the demands of ThyssenKrupp Steel Europe.

Problem: The vast amount of actors involved in shipping international sea freight containers results in logistics and security challenges.

Identify security and logistics challenges
Design of business processes that integrate advanced tracking technology
Assess potential of advanced tracking technology to tackle security and logistics challenges

Methodology
Expert Interviews
Modelling of processes using event-driven process chain modelling (EPC)
Value benefit analysis to evaluate integration of tracking technology

Results

Formalized process models of the as-is processes in the international sea freight container supply chain
Identification of 4 logistics and 3 security major challenges (e.g., distributed data, low standardization)
Design of target processes that integrate tracking solutions to tackle the logistics and security challenges

Problem:

The objective of this R & D project was the evaluation of process improvements in the warehouse management.
Against the background of a possible outsourcing of warehouse management to a logistics service provider an improved in-house solution should be compared to a possible outsourcing scenario.

Methodology
Process analysis in expert interviews and on-site inspection
Event-driven process chains, verified in interview rounds
Participatory system analysis
Process improvements in materials management, inventory management and in developing target processes
Cost-benefit assessments
Stock analysis with throughput diagrams and inventory operating curves

Results

Identification of logstics improvement potentials
Development of concept for in-house sourcing